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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted alphabetically
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 61)
Annals of Applied Statistics     Full-text available via subscription   (Followers: 39)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Argumentation et analyse du discours     Open Access   (Followers: 10)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 8)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 4)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 13)
Bernoulli     Full-text available via subscription   (Followers: 9)
Biometrical Journal     Hybrid Journal   (Followers: 10)
Biometrics     Hybrid Journal   (Followers: 51)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 18)
Building Simulation     Hybrid Journal   (Followers: 1)
Bulletin of Statistics     Full-text available via subscription   (Followers: 4)
CHANCE     Hybrid Journal   (Followers: 5)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 11)
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 37)
Current Research in Biostatistics     Open Access   (Followers: 8)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 11)
Demographic Research     Open Access   (Followers: 16)
Electronic Journal of Statistics     Open Access   (Followers: 8)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
ESAIM: Probability and Statistics     Full-text available via subscription   (Followers: 5)
Extremes     Hybrid Journal   (Followers: 2)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 5)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
International Journal of Quality, Statistics, and Reliability     Open Access   (Followers: 17)
International Journal of Stochastic Analysis     Open Access   (Followers: 3)
International Statistical Review     Hybrid Journal   (Followers: 12)
International Trade by Commodity Statistics - Statistiques du commerce international par produit     Full-text available via subscription  
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 4)
Journal of Applied Statistics     Hybrid Journal   (Followers: 20)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 20)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 39, SJR: 3.664, CiteScore: 2)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 20)
Journal of Econometrics     Hybrid Journal   (Followers: 82)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 6)
Journal of Forecasting     Hybrid Journal   (Followers: 17)
Journal of Global Optimization     Hybrid Journal   (Followers: 7)
Journal of Interactive Marketing     Hybrid Journal   (Followers: 10)
Journal of Mathematics and Statistics     Open Access   (Followers: 8)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Journal of Probability and Statistics     Open Access   (Followers: 10)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 32)
Journal of Statistical and Econometric Methods     Open Access   (Followers: 5)
Journal of Statistical Physics     Hybrid Journal   (Followers: 13)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 8)
Journal of Statistical Software     Open Access   (Followers: 20, SJR: 13.802, CiteScore: 16)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 72, SJR: 3.746, CiteScore: 2)
Journal of the Korean Statistical Society     Hybrid Journal   (Followers: 1)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 31)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 26)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 43)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 16)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 30)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Lifetime Data Analysis     Hybrid Journal   (Followers: 7)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Metrika     Hybrid Journal   (Followers: 4)
Modelling of Mechanical Systems     Full-text available via subscription   (Followers: 1)
Monte Carlo Methods and Applications     Hybrid Journal   (Followers: 6)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 2)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 5)
Optimization Letters     Hybrid Journal   (Followers: 2)
Optimization Methods and Software     Hybrid Journal   (Followers: 8)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 34)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Probability Surveys     Open Access   (Followers: 4)
Queueing Systems     Hybrid Journal   (Followers: 7)
Research Synthesis Methods     Hybrid Journal   (Followers: 7)
Review of Economics and Statistics     Hybrid Journal   (Followers: 124)
Review of Socionetwork Strategies     Hybrid Journal  
Risk Management     Hybrid Journal   (Followers: 15)
Sankhya A     Hybrid Journal   (Followers: 2)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Sequential Analysis: Design Methods and Applications     Hybrid Journal  
Significance     Hybrid Journal   (Followers: 7)
Sociological Methods & Research     Hybrid Journal   (Followers: 37)
SourceOCDE Comptes nationaux et Statistiques retrospectives     Full-text available via subscription  
SourceOCDE Statistiques : Sources et methodes     Full-text available via subscription  
SourceOECD Bank Profitability Statistics - SourceOCDE Rentabilite des banques     Full-text available via subscription   (Followers: 1)
SourceOECD Insurance Statistics - SourceOCDE Statistiques d'assurance     Full-text available via subscription   (Followers: 2)
SourceOECD Main Economic Indicators - SourceOCDE Principaux indicateurs economiques     Full-text available via subscription   (Followers: 1)
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  
SourceOECD Monthly Statistics of International Trade     Full-text available via subscription   (Followers: 1)
SourceOECD National Accounts & Historical Statistics     Full-text available via subscription  
SourceOECD OECD Economic Outlook Database - SourceOCDE Statistiques des Perspectives economiques de l'OCDE     Full-text available via subscription   (Followers: 2)
SourceOECD Science and Technology Statistics - SourceOCDE Base de donnees des sciences et de la technologie     Full-text available via subscription  
SourceOECD Statistics Sources & Methods     Full-text available via subscription   (Followers: 1)
SourceOECD Taxing Wages Statistics - SourceOCDE Statistiques des impots sur les salaires     Full-text available via subscription  
Stata Journal     Full-text available via subscription   (Followers: 9)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Statistical Applications in Genetics and Molecular Biology     Hybrid Journal   (Followers: 5)
Statistical Communications in Infectious Diseases     Hybrid Journal  
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Statistical Methodology     Hybrid Journal   (Followers: 7)
Statistical Methods and Applications     Hybrid Journal   (Followers: 6)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 27)
Statistical Modelling     Hybrid Journal   (Followers: 19)
Statistical Papers     Hybrid Journal   (Followers: 4)
Statistical Science     Full-text available via subscription   (Followers: 13)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Statistics & Risk Modeling     Hybrid Journal   (Followers: 2)
Statistics and Computing     Hybrid Journal   (Followers: 13)
Statistics and Economics     Open Access   (Followers: 1)
Statistics in Medicine     Hybrid Journal   (Followers: 191)
Statistics, Politics and Policy     Hybrid Journal   (Followers: 6)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 14)
Stochastic Models     Hybrid Journal   (Followers: 3)
Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports     Hybrid Journal   (Followers: 2)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Teaching Statistics     Hybrid Journal   (Followers: 7)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
TEST     Hybrid Journal   (Followers: 3)
The American Statistician     Full-text available via subscription   (Followers: 24)
The Annals of Applied Probability     Full-text available via subscription   (Followers: 8)
The Annals of Probability     Full-text available via subscription   (Followers: 10)
The Annals of Statistics     Full-text available via subscription   (Followers: 34)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 11)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)

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Journal Cover
Engineering With Computers
Journal Prestige (SJR): 0.485
Citation Impact (citeScore): 2
Number of Followers: 5  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1435-5663 - ISSN (Online) 0177-0667
Published by Springer-Verlag Homepage  [2626 journals]
  • A novel systematic and evolved approach based on XGBoost-firefly algorithm
           to predict Young’s modulus and unconfined compressive strength of rock
    • Abstract: Abstract To design the tunnel excavations, the most important parameters are the engineering properties of rock, e.g., Young’s modulus (E) and unconfined compressive strength (UCS). Numerous researchers have attempted to propose methods to estimate E and UCS indirectly. This task is complex due to the difficulty of preparing and carrying out such experiments in a laboratory. The main aim of the present study is to propose a new and efficient machine learning model to predict E and UCS. The proposed model combines the extreme gradient boosting machine (XGBoost) with the firefly algorithm (FA), called the XGBoost-FA model. To verify the feasibility of the XGBoost-FA model, a support vector machine (SVM), classical XGBoost, and radial basis function neural network (RBFN) were also employed. Forty-five granite sample sets, collected from the Pahang-Selangor tunnel, Malaysia, were used in the modeling. Several statistical functions, such as coefficient of determination (R2), mean absolute percentage error (MAPE) and root mean square error (RMSE) were calculated to check the acceptability of the methods mentioned above. A review of the results of the proposed models revealed that the XGBoost-FA was more feasible than the others in predicting both E and UCS and could generalize.
      PubDate: 2021-01-16
       
  • Lyapunov–Sylvester computational method for numerical solutions of a
           mixed cubic-superlinear Schrödinger system
    • Abstract: Abstract In this paper a nonlinear coupled Schrödinger system in the presence of mixed cubic and superlinear power laws is considered. A non standard numerical method is developed to approximate the solutions in higher dimensional case. The idea consists in transforming the continuous system into an algebraic quasi linear dynamical discrete one leading to generalized semi-linear operators. Next, the discrete algebraic system is studied for solvability, stability and convergence. At the final step, numerical examples are provided to illustrate the efficiency of the theoretical results.
      PubDate: 2021-01-16
       
  • Dynamic simulation of moderately thick annular system coupled with shape
           memory alloy and multi-phase nanocomposite face sheets
    • Abstract: Abstract The current research work analyzes dynamics of a sandwich disk which is gently thick. The mentioned sandwich structure has honeycomb core, a couple of middle layers having fibers of shape memory alloy (SMA), and a couple of external layers of multi-scaled hybrid nanocomposite (MHC) considering in-plane force. The core in the shape of honeycomb is manufactured of aluminum due to its high stiffness and less density compared with other materials. Applying energy methods called the principle of Hamilton, we obtained governing motion equations of the mentioned structure and solved them using First-order shear-deformation-theory (FSDT), as well as generalized-differential-quadrature-method (GDQM), respectively. To layers’ joint, the compatibility equations have been taken into account. Then, a parametric mathematical manipulation has been conducted to analyze the impacts of fibers of SMA, boundary conditions (BCs), internal loads, honeycomb network angle, ratio of external to internal radiuses, ratio of thickness to length of the honeycomb, weight fraction of CNTs, angle of fibers, ratio of honeycomb to face-sheet thickness on the frequency of the multi-phase sandwich disk. The outcomes derived reveal that for any amount of internal pressure and each BCs, the relation of the honeycomb’s thickness ratios to MHC layer ( \({h}_{H}/{h}_{t}\) ) and sandwich structure’s frequency is similar to quadratic function. Further results show that the effects of the fibers’ angle on the frequency can be ignored for larger \({h}_{H}/{h}_{t}\) amounts.
      PubDate: 2021-01-13
       
  • Trefftz-unsymmetric finite element for bending analysis of orthotropic
           plates
    • Abstract: Abstract This work develops a new four-node quadrilateral displacement-based Trefftz-type plate element for bending analysis of orthotropic plates within the framework of the unsymmetric finite element method (FEM). In the present formulation, the modified isoparametric interpolations are employed to formulate the element’s test functions in which the deflection is effectively enriched by the nodal rotation degrees of freedom (DOFs). Meanwhile, the element’s trial functions are determined based on the Trefftz functions that can a prior satisfy the governing equations of orthotropic Mindlin–Reissner plates. Numerical benchmark tests reveal that the new unsymmetric plate element is free of shear locking problem and can produce satisfactory results for both the displacement and stress resultant. In particular, it exhibits quite good tolerances to the gross mesh distortion.
      PubDate: 2021-01-12
       
  • A novel truly explicit time-marching procedure for simple and effective
           analyses of wave propagation models
    • Abstract: Abstract In this paper, a novel explicit time-marching procedure is proposed for wave propagation analysis. The new method is extremely simple to implement and highly effective, providing a very attractive formulation. It considers staggered forward and backward finite difference expressions to approximate the derivative fields of the model, as well as it introduces adaptive corrections into the computations, improving the accuracy and the stability of the analysis. The novel approach is truly explicit (all force terms are treated explicitly), truly self-starting, and it enables adaptive algorithm dissipation. In fact, the proposed technique stands as a single-step approach that adapts itself (taking into account a highly straightforward algorithm) according to the computed responses, the physical properties of the model and the adopted temporal and spatial discretizations. Numerical results are presented at the end of the paper, illustrating the excellent performance of the novel formulation, considering different (linear and nonlinear) wave propagation models.
      PubDate: 2021-01-11
       
  • Fuzzy Shannon wavelet finite element methodology of coupled heat transfer
           analysis for clearance leakage flow of single screw compressor
    • Abstract: Abstract The Shannon wavelet function and its scale function are used as interpolating functions to establish the Shannon wavelet finite element. The temperature and velocity of every leakage path are calculated based on fuzzy Shannon wavelet finite element method, fuzzy Daubechies wavelet finite element model, fuzzy finite element method and experiment, and comparisons between numerical analysis results and experimental results show that fuzzy Shannon-cosine wavelet finite element method can get highest computing precision and accuracy. The coupling relationships between the flow and heat transfer of clearance leakage flow are analyzed based on fuzzy Shannon-cosine finite element method, and numerical results show that the Nusselt number of every leakage path decreases with increase of Mach number, the flow has great influence on heat transfer of clearance leakage flow of single screw compressor.
      PubDate: 2021-01-11
       
  • Automatic Delaunay mesh generation method and physically-based mesh
           optimization method on two-dimensional regions
    • Abstract: Abstract Delaunay mesh generation method is a common method for unstructured mesh (or unstructured grid) generation. Delaunay mesh generation method can conveniently add new points to the existing mesh without remeshing the whole domain. However, the quality of the generated mesh is not high enough if compared with some mesh generation methods. To obtain high-quality mesh, this paper developed an automatic Delaunay mesh generation method and a physically-based mesh optimization method on two-dimensional regions. For the Delaunay mesh generation method, boundary-conforming problem was ensured by create nodes at centroid of mesh elements. The definition of node bubbles and element bubbles was provided to control local mesh coarseness and fineness automatically. For the physically-based mesh optimization method, the positions of boundary node bubbles are predefined, the positions of interior node bubbles are adjusted according to interbubble forces. Size of interior node bubbles is further adjusted according to the size of adjacent node bubbles. Several examples show that high-quality meshes are obtained after mesh optimization.
      PubDate: 2021-01-10
       
  • Spiral water cycle algorithm for solving multi-objective optimization and
           truss optimization problems
    • Abstract: Abstract This paper addresses multi-objective optimization and the truss optimization problem employing a novel meta-heuristic that is based on the real-world water cycle behavior in rivers, rainfalls, streams, etc. This meta-heuristic is called multi-objective water cycle algorithm (MOWCA) which is receiving great attention from researchers due to the good performance in handling optimization problems in different fields. Additionally, the hyperbolic spiral movement is integrated into the basic MOWCA to guide the agents throughout the search space. Consequently, under this hyperbolic spiral movement, the exploitation ability of the proposed MOSWCA is promoted. To assess the robustness and coherence of the MOSWCA, the performance of the proposed MOSWCA is analysed on some multi-objective optimisation benchmark functions; and three truss structure optimization problems. The results obtained by the MOSWCA of all test problems were compared with various multi-objective meta-heuristic algorithms reported in the literature. From the empirical results, it is evident that the suggested approach reaches an excellent performance when solving multi-objective optimization and the truss optimization problems.
      PubDate: 2021-01-07
       
  • Solving the stochastic support vector regression with probabilistic
           constraints by a high-performance neural network model
    • Abstract: Abstract This paper offers a recurrent neural network to support vector machine (SVM) learning in stochastic support vector regression with probabilistic constraints. The SVM is first converted into an equivalent quadratic programming (QP) formulation in linear and nonlinear cases. An artificial neural network for SVM learning is then proposed. The presented neural network framework guarantees obtaining the optimal solution of the SVM problem. The existence and convergence of the trajectories of the network are studied. The Lyapunov stability for the considered neural network is also shown. The efficiency of the proposed method is shown by three illustrative examples.
      PubDate: 2021-01-07
       
  • SChoA: an newly fusion of sine and cosine with chimp optimization
           algorithm for HLS of datapaths in digital filters and engineering
           applications
    • Abstract: Abstract The Chimp optimization algorithm (ChoA) inspired by the individual intelligence and sexual motivation of chimps in their group hunting, which is separate from the another social predators. Generally, it is developed for trapping in local optima on the complex functions and alleviate the slow convergence speed. This algorithm has been widely applied to find the best optima solutions of complex global optimization tasks due to its simplicity and inexpensive computational overhead. Nevertheless, premature convergence is easily trapped in the local optimum solution during search process and is ineffective in balancing exploitation and exploration. In this paper, we have developed a modified novel nature inspired optimizer algorithm based on the sine–cosine functions; it is called as sine–cosine chimp optimization algorithm (SChoA). During this research, the sine–cosine functions have been applied to update the equations of chimps during the search process for reducing the several drawbacks of the ChoA algorithm such as slow convergence rate, locating local minima rather than global minima, and low balance amid exploitation and exploration. Experimental solutions based on 23-standard benchmark and 06 engineering functions such as welded beam, tension/compression spring, pressure vessel, multiple disk clutch brake, planetary gear train and digital filters design, etc. demonstrate the robustness, effectiveness, efficiency, and convergence speed of the proposed algorithm in comparison with others.
      PubDate: 2021-01-07
       
  • Bending and stress responses of the hybrid axisymmetric system via
           state-space method and 3D-elasticity theory
    • Abstract: Abstract This research presents bending responses of hybrid laminated nanocomposite reinforced axisymmetric circular/annular plates (HLNRACP/ HLNRAAP) within the framework of non-polynomial under mechanical loading and various type of initially stresses via the three-dimensional elasticity theory. The current structure is on the Pasternak type of elastic foundation and torsional interaction. The state-space approach and differential quadrature method (SS-DQM) are studied to present the bending characteristics of the current structure by considering various boundary conditions. To predict the material properties of the bulk, the role of mixture and Halpin–Tsai equations are studied. For modeling the circular plate, a singular point is studied. Finally, a parametric study investigates the impacts of various types of distribution of laminated layers, stacking sequence on the stress/strain information of the HLNRACP/ HLNRAAP. Results reveal that the system's static stability and bending behavior improve due to increasing the value of Winkler and Pasternak factors, and the stress distribution becomes more uniform.
      PubDate: 2021-01-06
       
  • Proposing several hybrid PSO-extreme learning machine techniques to
           predict TBM performance
    • Abstract: Abstract A proper planning schedule for tunnel boring machine (TBM) construction is considered as a necessary and difficult task in tunneling projects. Therefore, prediction of TBM performance with high degree of accuracy is needed to prepare a suitable planning schedule. This study aims to predict the advance rate of TBMs using optimized extreme learning machine (ELM) model with six particles swam optimization (PSO) techniques. Hence, six deterministically adaptive models, including time-varying acceleration (TAC)–PSO–ELM, improved PSO–ELM, Modified PSO–ELM, TAC–MeanPSO–ELM, improved MeanPSO–ELM, and Modified MeanPSO–ELM were developed. A number of performance criteria along with ranking system were used to identify the best model. The results showed that modified MeanPSO–ELM achieved the highest cumulative ranking (56), while the modified PSO–ELM achieved the lowest cumulative ranking (51). For training phase, improved PSO–ELM and TAC–PSO–ELM achieved the highest ranking (30) for each. The TAC–MeanPSO–ELM obtained the lowest ranking in the testing phase (29). Concerning the coefficient of determination (R2), modified PSO–ELM, improved PSO–ELM, TAC–PSO–ELM, and modified MeanPSO–ELM showed a similar behavior and achieved 0.97 for training and 0.96 for testing phases. Two models, including improved MeanPSO–ELM and TAC–MeanPSO–ELM achieved the same R2 of 0.96 for both training and testing phases. The findings of this study suggest that the hybridization of ELM and PSO may result in more accurate results than single ELM model to predict the TBM advance rate.
      PubDate: 2021-01-05
       
  • A third order shear deformable model and its applications for nonlinear
           dynamic response of graphene oxides reinforced curved beams resting on
           visco-elastic foundation and subjected to moving loads
    • Abstract: Abstract In present work, a nonlinear functionally graded curved beam model including the von Kármán geometric nonlinearity is developed on the basis of the third-order shear deformation theory. Due to incorporating the trapezoidal shape factor in the proposed model, the errors caused by geometric curvatures are eliminated. The governing equations of motions related to the dynamics of curved beams are derived by Lagrange method and solved using a standard Newmark time iteration procedure in conjunction with Newton–Raphson technique. Some comparisons are performed and indicate that the results from our model coincide favorably with semi-analytical solutions. Afterwards, utilizing the proposed model, the present investigation focuses on the nonlinear transient response of functionally graded multilayer curved beams reinforced by graphene oxide nano-fillers subjected to moving loads. A modified Halpin–Tsai micromechanical model is implemented to determine the effective modulus of graphene oxide/polymer nanocomposite, and the rule of mixture is used to calculate the mass density and Poisson’s ratio. The curved beams are assumed to rest on a visco-Pasternak foundation. The effects GO nano-fillers, including their weight fractions, distribution patterns and size on the nonlinear dynamic responses of the nanocomposite curved beams subjected to moving loads are studied. Moreover, the effects of radius-to-span ratios and visco-Pasternak foundation on the nonlinear dynamic response of curved beams are also discussed as subtopics.
      PubDate: 2021-01-05
       
  • An efficient population-based simulated annealing algorithm for 0–1
           knapsack problem
    • Abstract: Abstract 0–1 knapsack problem (KP01) is one of the classic variants of knapsack problems in which the aim is to select the items with the total profit to be in the knapsack. In contrast, the constraint of the maximum capacity of the knapsack is satisfied. KP01 has many applications in real-world problems such as resource distribution, portfolio optimization, etc. The purpose of this work is to gather the latest SA-based solvers for KP01 together and compare their performance with the state-of-the-art meta-heuristics in the literature to find the most efficient one(s). This paper not only studies the introduced and non-introduced single-solution SA-based algorithms for KP01 but also proposes a new population-based SA (PSA) for KP01 and compares it with the existing methods. Computational results show that the proposed PSA is the most efficient optimization algorithm for KP01 among all SA-based solvers. Also, PSA’s exploration and exploitation are stronger than the other SA-based algorithms since it generates several initial solutions instead of one. Moreover, it finds the neighbor solutions based on the greedy repair and improvement mechanism and uses both mutation and crossover operators to explore and exploit the solution space. Suffice to say that the next version of SA algorithms for KP01 can be enhanced by designing a population-based version of them and choosing the greedy-based approaches for the initial solution phase and local search policy.
      PubDate: 2021-01-05
       
  • A novel method for accurate simulations of concentrated forces in finite
           element analysis
    • Abstract: Abstract In this paper, the analytical displacement solution at the point of the application of a concentrated force is derived using elastic mechanics. Then, the concentrated-force asymptotic function is obtained. Next, by introducing the concentrated-force asymptotic functions into finite element analysis, a method of simulating concentrated forces is developed. The proposed method can obtain an accurate stress field without any mesh refinement at the point of the application of a concentrated force. Meanwhile, the proposed method has considered the effect of the direction of the concentrated forces. The numerical tests reveal that the proposed method is convergent, accurate and feasible for obtaining satisfactory results.
      PubDate: 2021-01-05
       
  • Chaotic optimization algorithm for performance-based optimization design
           of composite moment frames
    • Abstract: Abstract In this paper, performance-based optimization design of steel concrete composite moment resistance frames is presented using a chaotic optimization algorithm based on Chebyshev chaotic map. The strategy is applied to two examples of an 8-story frame and a 20-story frame. The structure is designed to respond to different levels of seismic hazard levels for the minimization of total weight. To achieve this goal, three main steps are conducted. In the first step, the five best designs for each of the frames were obtained by solving the optimization problem. Nonlinear pushover analysis was conducted to arrive at each performance level. In the next step, the fragility curves are plotted for five selected designs for each frame, and finally, damage margin ratios were calculated for each damage level and the best design for each frame was selected based on the damage margin ratio values. Results illustrate a desirable performance of the algorithms in both obtaining lower weight and selecting the best design based on the seismic behavior of the structure.
      PubDate: 2021-01-04
       
  • Novel approach to evaluate rock mass fragmentation in block caving using
           unascertained measurement model and information entropy with flexible
           credible identification criterion
    • Abstract: Abstract In recent years, block caving has drawn the attention of many mine enterprises due to the admired extraction rate and lower cost, which can exploit the materials via gravity inflow. At the same time, the limitation of this advanced method cannot be underestimated easily, such as surface subsidence and boulder, usually, the latter leads to the frequent secondary blast and damage of bottom structure. Thus, it is significant and crucial to evaluate the fragmentation before the implement of this method. But, traditional fragmentation assessment model suffers from the complex process of modeling and simulation. In this study, a hybrid model consists of unascertained measurement theory and information entropy was constructed to meet the requirements of this prospective mining method. Considering the influence of various parameters on rock fragmentation at the same time, twenty-three factors (i.e., uniaxial compressive strength, modulus ratio, fracture frequency, aperture, persistence, joint orientation, roughness, infilling, weathering, in situ stresses, stress orientation, stress ratio, underground water, fine ratio, hydraulic radius, undercut height, draw column height, draw points geometry, draw rate, multiple draw interaction, air gap height, broken ore density and undercut direction) were chosen to extract the main characteristics of rock mass samples from the two different mines, namely Reserve North (Chile), Diablo Regimiento (Chile) and Kemess mine (Canada). A new membership function (logarithm curve) was added to eliminate uncertainty results from the low level of knowledge about rock mass properties. Then, information entropy was performed to quantify the impacts of individual index. A credible degree identification criterion (Rη) was also applied to review the sample attributes qualitatively. Ultimately, degree of fragmentation of the three samples was judged easily on the basis of a composite measurement vectors and Rη. The evaluation results showed that the fragmentation grades of Reserve North, Diablo Regimiento and Kemess mine, separately, were “Good”, “Medium” and “Good”. With regard to the excellent performance of this hybrid model, it can be seen as a reliable approach to describe the fragmentation potential during the ore extraction using block caving mining method.
      PubDate: 2021-01-04
       
  • Colliding bodies optimization with Morlet wavelet mutation and quadratic
           interpolation for global optimization problems
    • Abstract: Abstract This paper represents a new variant of colliding bodies optimization (CBO) and the objective is to alleviate the lack of population diversity, premature convergence phenomenon, and the imbalance between the diversification and intensification of the CBO method. The CBO is a meta-heuristic algorithm based on momentum and energy laws in a one-dimensional collision between two bodies. The proposed method is designed by hybridization of the CBO with Morlet wavelet (MW) mutation and quadratic interpolation (QI) (MWQI-CBO). The Morlet wavelet mutation is employed to improve the CBO so that it can explore the search space more effectively on reaching a better solution. Besides, quadratic interpolation that utilized historically best solution is added to CBO to enhance the exploitation phase. Two new parameters are defined to have a better balance between the diversification and the intensification inclinations. The proposed algorithm is tested in 24 mathematical optimization problems including 30 design variables and compared with standard CBO and some state-of-art metaheuristics. Besides, the optimal design of five standard discrete and continuous structural design problems with various constraints such as strength, stability, displacement, and frequency constraints are studied. It is found that MWQI-CBO is quite competitive with other meta-heuristic algorithms in terms of reliability, solution accuracy, and convergence speed.
      PubDate: 2021-01-04
       
  • A modified multi-level cross-entropy algorithm for optimization of
           problems with discrete variables
    • Abstract: Abstract Nowadays, the advancement of technology and the increase in the power of computer processing have enabled using these processors to solve different problems in the shortest possible time. Many scholars throughout the world seek to shorten the time needed to solve various problems. As engineering science has a wide range of problems with different natures, it is impossible to claim whether a particular method can solve all the problems faced. Considering the aim of developing optimization methods, in this study, a new method is used by combining a multi-level cross-entropy optimizer (MCEO) algorithm with sigmoid functions to smooth the space of the problems with discrete variables. It is named modified multi-level cross-entropy optimizer (MMCEO). Four problems including designing vessel, speed reducer, 15-member, and 52-member trusses were considered to examine the effectiveness of the proposed algorithm in dealing with various problems. It is of note that all of these problems have discrete variables and they are defined in very difficult spaces. The results regarding the first two problems (i.e., pressure vessel and speed reducer) indicated the very high accuracy of the proposed method and the improvement of the response (in terms of function calls) and in trusses designing. Moreover, they suggested its higher speed compared to the best algorithms in designing the stated structures.
      PubDate: 2021-01-03
       
  • Fault diagnosis of a nonlinear hybrid system using adaptive unscented
           Kalman filter bank
    • Abstract: Abstract In this paper, a model-based fault diagnosis scheme of a nonlinear hybrid system using an adaptive unscented Kalman filter (AUKF) bank is proposed. The hybrid system is an amalgamation of discrete dynamics and continuous states. Fault diagnosis for simultaneous occurrences of multiple faults such as leakage fault, clogging fault, sensor fault, and actuator fault on a benchmark three-tank system are simulated. The residual signal based output generates some discrete modes that guarantee the uniqueness of the concerning fault. The efficacy of the proposed scheme is compared with that of the adaptive extended Kalman filter (AEKF) bank on the same system to prove its better response over AEKF.
      PubDate: 2021-01-03
       
 
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