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  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
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Applied Mathematics and Nonlinear Sciences
Number of Followers: 1  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2444-8656
Published by Sciendo Homepage  [371 journals]
  • Design of language assisted learning model and online learning system
           under the background of artificial intelligence

    • Abstract: This paper aiming at the problems of scattered operation types, poor extraction effect of learning resources and incomplete assignment of learning tasks in the online language learning platform designs a language assisted learning model under the background of artificial intelligence, proposes an English learning resource extraction algorithm based on the integration of LSA and N-gram models and then proposes a weighted multi-task learning model and it is optimized to improve the sparsity of learning variables. Finally, based on the construction of the assisted learning model, the online language learning system is designed, including demand analysis, overall design and architecture design, to improve the pertinence and efficiency of English learning.
      PubDate: Thu, 10 Nov 2022 00:00:00 GMT
       
  • Research on innovative strategies of college students’ English teaching
           under the blessing of big data

    • Abstract: The rapid development of modern society is inseparable from information technology, and most of this information technology is based on big data, which makes the teaching field in the new era keep pace with the times and brings great changes to the academic activities in which teachers and students participate, as well as to the quality of their thinking skills, and thus, likely even their overall lives. Under the background of big data, through the effective application of relevant technologies, students’ learning is no longer limited to a relatively single traditional teaching level, and teaching needs strategic innovation. This paper improves the mathematical model of precision teaching strategy, establishes the empirical model of the optimal mode of College English teaching based on big data and puts forward relevant innovative teaching methods. Through the rational use of big data technology, the content and form of College English classroom teaching can be improved, so as to improve the quality of College English teaching.
      PubDate: Fri, 21 Oct 2022 00:00:00 GMT
       
  • Optimisation of construction mode of residential houses based on the
           genetic algorithm under BIM technology

    • Abstract: BIM technology is a breakthrough in the construction industry whose application is of great value, and the engineering design, engineering budget and cost control combined with BIM technology have been developed rapidly. Therefore, in this paper, BIM technology is adopted to optimise the construction mode, and the genetic algorithm is selected to solve the scheduling model of construction. By applying an interdisciplinary research method combined with computer science and technology, an intelligent optimisation model of construction can provide a new research perspective and technical method for the development of the construction industry.
      PubDate: Fri, 21 Oct 2022 00:00:00 GMT
       
  • Research on multi-dimensional optimisation design of user interface under
           Rhino/GH platform

    • Abstract: With the rapid development of computer science and technology, there is an increasing diversity observed in the use of electronic computers. Users browse interactive content such as text, images, audio, video, etc. The increase of the interactive interface results in a slow interface response and affects the user experience. Therefore, this paper mainly studies the user interface under the multi-dimensional optimisation of the Rhino/GH platform, and introduces the long short-term memory and gated recurrent unit algorithms in the visualisation part for optimisation; the study results suggest that the overall response time is 50% but lower than the traditional interface, and the time fluctuation is within 23.7%, which is 23.6% but lower than the traditional 47.3%. When interacting with multiple interfaces, the interaction interface optimised by the Rhino/GH platform maintains a fluctuation range within 29.2%, and the time increases by 13 ms, showing excellent stability and efficiency.
      PubDate: Fri, 21 Oct 2022 00:00:00 GMT
       
  • Numerical simulation of vortex vibration in main girder of cable-stayed
           bridge based on bidirectional fluid–structure coupling

    • Abstract: Under the wind load, a structure produces the vortex vibration effect, which threatens the safety and durability of a bridge. Because of its low wind speed and high frequency, it poses a serious safety hazard to safety in the construction state and the traffic safety in the completed state. Therefore, in this paper, a numerical simulation method of vortex-introduced vibration (VIV) performance in the main girder of cable-stayed bridge based on bidirectional fluid-solid coupling is proposed. Taking CFD control equation as the constraint condition, the main girder model is divided into the calculation domain, grid division and boundary condition setting using the Gambit pre-processing software, and a vortex-induced force (VIF) model of the main girder based on the simulation process is proposed. Finally, based on the parameters of the main girder section model, the numerical simulation results of the vortex vibration performance of the main girder are analysed, and the results show that the vortex vibration test results are basically consistent.
      PubDate: Fri, 21 Oct 2022 00:00:00 GMT
       
  • Comparative analysis of CR of ideological and political education in
           different regions based on improved fuzzy clustering

    • Abstract: Vigorously developing ideological and political education (IPE) is the only way to boost talent training, and scientific and technological progress, and lead to the upgrading of the economic structure. Therefore, by analysing the internal relationship between the current social and economic growth and the development of IPE in colleges, this article introduces the investment of IPE into the social production function model where the gravity search method is used to optimise fuzzy clustering, and the classified data sets of each province in China are determined by genetic algorithm. In addition, the calculation model of contribution rate (CR) of IPE in different regions based on an improved fuzzy clustering algorithm is established, and the influence of IPE on regional economic development in eastern, western and central regions is compared and analysed, which is helpful to realise the optimal allocation of educational resources in China.
      PubDate: Fri, 21 Oct 2022 00:00:00 GMT
       
  • Game theoretic model for low carbon supply chain under carbon emissions
           reduction sensitive random demand

    • Abstract: This paper considers a low carbon supply chain consisting of a single manufacturer and a single retailer under the condition that the demand is uncertain. We first establish three games, including manufacturer Stackelberg (MS), retailer Stackelberg (RS) and Nash according to the different power structure of the firms. We then determine that the equilibrium stocking factors, emission reduction levels, wholesale prices and retail prices for the three models, respectively. After that, we demonstrate the effects of power structure. Results show that when the power shifts from the retailer to the manufacturer, the stocking factor decreases, whereas the wholesale price increases. Finally, we discuss the impacts of the random demand. We find that the expected profits of the firms, the emission reduction levels and the retail prices are increasing with respect to the market potential and low-carbon sensitivity coefficient, respectively. Meanwhile, they decrease with respect to the price sensitivity coefficient.
      PubDate: Fri, 14 Oct 2022 00:00:00 GMT
       
  • Similarity Solutions of the Surface Waves Equation in (2+1) Dimensions and
           Bifurcation

    • Abstract: The equation of the surface waves in deep water, given here by (1), is extended to (2+1) dimensions, which is a novel equation.. It is shown that the surface waves equation is self- free source. So, it has a class of infinite solutions. Here many types of self-similar and semi-self similar solutions are obtained. The self-similar waves show various geometric structures. Among them, wave crest in the form of coupled lumps and soliton wave moving along the characteristic curve in the plane. It is entrained by troughs with cavities. The semi-self similar waves exhibit multi lumps or periodic waves with troughs and multi-periodic waves. The study of bifurcation shows that the trajectories are open, so that the traveling wave solutions are unstable. The time-dependent steepness-function is defined here and it is found that it attains a maximum value and then it decreases with time. The results found are interesting in ocean engineering and sciences. The extended unified method is used, here, to find the exact solutions, which was proposed recently.
      PubDate: Fri, 14 Oct 2022 00:00:00 GMT
       
  • Optimal decisions and channel coordination of a green supply chain with
           marketing effort and fairness concerns

    • Abstract: This paper addresses the optimal decisions and channel coordination issues in a green supply chain composed of a socially responsible manufacturer and a fair-mined retailer, where the manufacturer invests in advanced facilities/technologies to improve green quality of products, and the retailer exerts marketing effort to enhance market demand. We develop supply chain models under three scenarios: centralized system, wholesale price (WP) contract without fairness concerns, and WP contract with fairness concerns. Our results show that the retailer’s fairness behavior further causes a benefit for herself, while the manufacturer and the total supply chain to suffer. Moreover, a revenue-cost-sharing (RCS) contract is introduced to coordinate supply chain. We prove that a win-win outcome is reachable, and the RCS contract is applicable in practice.
      PubDate: Fri, 14 Oct 2022 00:00:00 GMT
       
  • A long command subsequence algorithm for manufacturing industry
           recommendation systems with similarity connection technology

    • Abstract: The manufacturing industry requires a unique recommendation system to suggest products and raw materials, but its performance is often poor in massive data environment. In order to solve the similarity connection problem of large-scale real-time data, the optimised incremental similarity connection method which is used to deal with streaming data can be used to concisely obtain the longest common additive sequence of two given input sequences. This paper, on the basis of the recursion equation, applies a very simple linear space algorithm to solve this problem and adopts new states to carry out similarity connection of incremental data. The experimental results demonstrate that this method can not only ensure the accuracy of real-time recommendation system but also greatly reduce the computed amount.
      PubDate: Fri, 30 Sep 2022 00:00:00 GMT
       
  • The internal mechanism of corporate social responsibility fulfillment
           affecting debt risk in China: analysis of intermediary transmission effect
           based on degree of debt concentration and product market competitive
           advantage

    • Abstract: This paper takes the degree of debt concentration and product market competitive advantage as intermediary variables to explore the internal mechanism of the impact of CSR fulfilment on firm debt risk. It is found that the fulfilment of CSR can reduce the debt risk of firms by dispersing the degree of debt concentration and enhancing the competitive advantage of product market. The mediating effect of the degree of debt concentration has a direct impact on the competitive advantage of a product market and is particularly obvious in private firms and firms in the eastern region of China.
      PubDate: Fri, 30 Sep 2022 00:00:00 GMT
       
  • Application of machine learning in stock selection

    • Abstract: With the development of artificial intelligence technology, machine learning has achieved very good results in the field of stock selection. This paper mainly studies the application of linear model, clustering, support vector machine, random forest, neural network and deep learning methods in the field of stock selection. The main contribution of this paper is to provide a new idea for traditional quantitative investors, so that they can build a more efficient stock selection model in practical application. The experimental results show that the stock selection model constructed by these six machine learning methods can obtain higher return and stability.
      PubDate: Tue, 20 Sep 2022 00:00:00 GMT
       
  • Research on an early warning model of effectiveness evaluation in
           ideological and political teaching based on big data

    • Abstract: Ideological and political (IAP) education is an important part of higher education, which plays a fundamental role in allround education mechanisms and other fields. Under the vigorous development of big data technology, the crisis of IAP teaching effectiveness in colleges and universities is restricted by the non-linear development path, incomplete information collection, irregular data distribution, difficulty in quantifying index design and so on. Therefore, by analysing the application foundation of big data in IAP teaching evaluation, this paper puts forward an early warning model of IAP teaching effectiveness based on SVM algorithm design and decision analysis of a BP neural network and quantifies the quality of IAP teaching by constructing an index system of IAP evaluation, early warning evaluation value and early warning limit value, which is helpful to realise all-round dynamic early warning of IAP education in colleges and universities.
      PubDate: Wed, 24 Aug 2022 00:00:00 GMT
       
  • Basketball Shooting Rate Based on Multiple Regression Logical-Mathematical
           Algorithm

    • Abstract: This paper proposes a mathematical model of multiple regression analysis of basketball shooting percentage. We give the numerical solution for the shooting angle under given solution conditions by solving the equation. From this, the optimal shooting speed and cut-off shooting speed under the shooting at a given point are obtained. At the same time, we analyze the laws of basketball movement in several different forms of rotation. The article combines Matlab software for verification to get the best angle of entry and the best shooting distance and speed.
      PubDate: Fri, 15 Jul 2022 00:00:00 GMT
       
  • Power Flow Calculation in Smart Distribution Network Based on Power
           Machine Learning Based on Fractional Differential Equations

    • Abstract: Based on the theory of fractional differential equations, this paper proposes a simple recursive, iterative scheme for power flow calculation in pure radial networks. The paper determines the network hierarchy formed by the ADT stack through breadth theory. This helps us define the branch sequence of the forward and backward generation in the power flow calculation of the smart distribution network. We ensure that the Jacobian matrix remains unchanged in the smart distribution grid power flow calculation. The interval model is more practical and computationally simpler than the point model. The research results show that the power flow calculation method is efficient based on the fractional differential equation.
      PubDate: Fri, 15 Jul 2022 00:00:00 GMT
       
  • Lagrange’s Mathematical Equations in the Sports Training of College
           Students

    • Abstract: Because the current sports group competition middle school students’ motion video recognition is complicated, the article uses Lagrangian mathematical equations to classify the motion videos. Based on the spatial smoothness of the flicker parameter function, this paper proposes a Lagrangian mathematical method for detecting local motion regions. The research results show that the motion differential equation and numerical calculation method of the video derived in the article are correct.
      PubDate: Fri, 15 Jul 2022 00:00:00 GMT
       
  • The Approximate Solution of Nonlinear Vibration of Tennis Based on
           Nonlinear Vibration Differential Equation

    • Abstract: In this paper, a nonlinear vibration differential equation is established for the moment when a tennis racket hits the ball. At the same time, we deduce the relationship between the tennis racket string tension and the separation time and distance of the hitting speed. Then the article analyzes the vibration equation of the tennis racket damping ball. We use ANSYS finite element analysis software for solid modeling and modal analysis of tennis rackets. The natural frequency of the tennis racket was obtained through the verification results of the experimental modal analysis. A qualitative relationship between the natural frequency of the vibration-absorbing ball system and some parameters was found.
      PubDate: Fri, 15 Jul 2022 00:00:00 GMT
       
  • Graphical Modular Power Technology of Distribution Network Based on
           Machine Learning Statistical Mathematical Equation

    • Abstract: The distribution network structure is complex, the equipment is numerous, and the frequency of pattern and mode changes is high. These characteristics lead to certain difficulties in power distribution automation operation and maintenance graph management. This paper adopts the mathematical statistics method of machine learning to analyze the multi-version hierarchical subscription mechanism of the distribution network graph. We conduct a breadth search on the distribution network graph to realize the automatic topology of the network. This paper implements a dynamic display system of distribution network monitoring information. The research results show that the graph-digital-analog integrated system has practical significance for data integration, application integration, and interoperability between systems.
      PubDate: Fri, 15 Jul 2022 00:00:00 GMT
       
  • Research on Detection Model of Abnormal Data in Engineering Cost List

    • Abstract: Projects of engineering construction have the characteristics of large investment and long cycle, which makes the cost management difficult and the data are often abnormal. Therefore, it is necessary to strengthen the detection of abnormal data in engineering cost list. Based on this, the establishment of a detection model of engineering cost list is studied in this paper. By introducing K-means clustering method into the model, the list is clustered according to the comprehensive unit cost, and the list data are classified by Bayesian list classification method where the value of k is selected as 5. The detection of abnormal data method in engineering cost list is compared with that of the traditional detection method based on distance, which is known that the detection model has good effect, high accuracy and recall rate.
      PubDate: Wed, 15 Jun 2022 00:00:00 GMT
       
  • Decisions of competing supply chain with altruistic retailer under risk
           aversion

    • Abstract: This paper considers the supply chain composed of altruistic retailers and selfish manufacturers under risk aversion. We use the mean variance (MV) method to construct two types of behavior models. One is a two-stage supply chain model with a single manufacturer and a single retailer, and the other is a competitive supply chain model with two retailers and two manufacturers. We discuss the decision-making problems under manufacturer Stackelberg (MS) game and retailer Stackelberg (RS) game, respectively. We analyze the role of risk aversion and power structure. Results show that the more risk aversion manufacturers are, the lower the emission reduction levels are. It also find that the prices increase with power shift from retailers to manufacturers. Finally, we point out that the competing can help the firms earn more benefits via numerical studies.
      PubDate: Fri, 29 Apr 2022 00:00:00 GMT
       
 
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