 Subjects -> CONSERVATION (Total: 128 journals)
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- Graphical Representation of Chemical Reactions and Heat Cascade Analysis
of Biomass Residue Syngasification to Produce Hydrogen-
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Abstract: The production of hydrogen by syngasification of biomass in Brazil provides a significant opportunity to increase the profitability of the sugarcane ethanol industry, as sugarcane biomass residues are available at low cost and in large quantities in the country. Hydrogen makes it possible to produce high-value chemicals from ethanol, whose production from sugarcane is already developed and energy efficient, and H2 can also be used as a transportation fuel. This article discusses the reaction thermodynamics of syngasification, proposes a C-H–O chart to analyze the chemical reactions, and analyzes the heat cascade through a syngasifier and the downstream operations for producing hydrogen. The proposed C-H–O chart makes it possible (1) to estimate the higher heating value of molecules involved in the syngasification, (2) to visualize the region of carbon deposit, (3) to represent the reactions occurring in a syngasifier and determine whether the enthalpy and entropy changes are positive or negative, and (4) to evaluate the effects of composition, pressure, and temperature on the reaction system. The tool also allows following the progressive changes in stream composition through process operations. For the first time, the heat cascade through each operation of the complete hydrogen-producing syngasification process has been analyzed. Results show that the chemical reactions release enough heat to satisfy all thermal demands of the downstream operations. Overall, purified hydrogen contains around 67% of the higher heating value of inlet biomass. Integrating the process that produces hydrogen with the process of making ethanol from sugarcane, whose bagasse would feed the hydrogen process, leads to a reduction of 20% of the total heat consumption. Graphical Chemical reactions occurring in an allothermal syngasifier The yellow diamond shows the global composition (mixture of biomass and steam). 
PubDate: 2023-06-07
- Productivity Enhancement of Solar Stills: a Review on Factors Affecting
the Performance of Solar Still-
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Abstract: In the coming decades, drinking water will become a serious global issue. Solar distillation has been used as a renewable solution for producing pure water from brackish/impure water. The low level of production that solar stills typically achieve is the primary drawback associated with solar distillation. As a result of this, the high freshwater demand cannot be met by solar distillation. This study provides an in-depth analysis and assessment of all the factors that affect solar distillation performance. The purpose of this study paper is to address the need for a complete investigation of the combined parameters impacting the performance of solar stills and their possible synergistic effects. Thus, it will reduce the authors’ effort and time spent identifying the shortcomings of previously utilized systems, allowing them to brainstorm innovative solutions that have not been previously investigated. This paper reviews the effect of solar radiation intensity, brackish water depth in the basin, temperature gradient between the water in the basin and the inclined glass cover, inclination angle of transparent glass, insulation used, wick materials, fins, reflectors, and modifications in the conventional solar still (CSS), on the performance of solar stills. According to the findings, the pyramidal solar still design, when equipped with appropriate modifications, has been observed to exhibit significantly enhanced efficiency, making it an attractive option for daily production of distillate at a rate of approximately 9–10 L/m2/day. The optimal yield for conventional solar stills can be achieved with a water depth of approximately 10 mm. It is possible to enhance the performance of a solar still by reducing the distance between the condensing cover and the absorber plates. The goal of this review is to provide researchers’ ideas so that they can choose appropriate strategies for increasing the productivity of solar stills. Finally, some suggestions for future research are made.
PubDate: 2023-06-05
- Coordinated Integration of Agricultural and Industrial Processes: a Case
Study of Sugarcane-Derived Production-
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Abstract: The coordinated integration of agricultural and industrial processes in plant-derived production can offer a solution toward sustainability. However, it is hard for general practitioners to realize the coordinated integration of these processes just based on the precedent fact. A special form clarifying the functions of the required activities should be shared among the practitioners for deliberate system design. In this study, a function model for coordinated integration was developed using the type-zero language of integrated definition for object-oriented design. Inputs, outputs, controls, and mechanisms for the required activities and the relationship between them were analyzed through modeling, after which the model was verified based on actual historical facts in the Japanese cane sugar industry. Finally, as a case study from a different industry, the applicability and limitation of the function model in the palm oil industry are discussed. Although the validity of the model should be confirmed through accumulating future case studies, the structure of the function model should be common to industrial crop-derived productions.
PubDate: 2023-05-24
- Multi-Energy Complementation Comprehensive Energy Optimal Dispatch System
Based on Demand Response-
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Abstract: The comprehensive energy system is constantly developing. How to meet the society and the environment as the premise and construct an optimal dispatch strategy is the main research direction of the current energy system development. In the study, multi-energy complementarity is considered, based on demand response, and a Multi-energy Complementation (MEC) optimal dispatch model is established based on Conditional value at risk (CVaR), and finally the energy system optimal dispatch test simulation evaluation under different circumstances is carried out. The simulation results show that the MEC comprehensive energy optimal dispatching system proposed in the study takes the demand side response into account, and the WP energy utilization of the system is more reasonable. When the demand side response is fully considered, the highest load value is 574.12 kW. After considering the demand side response and carbon emission, the average daily carbon emission of the system is only 59.36 kg. When the demand side response and carbon footprint are not considered, the carbon footprint of the gas-fired boiler in the system is always maintained at 32.31 kg, and the carbon emission is small. The comparison of the energy optimal dispatching system shows that the system cost proposed by the research is only 8880.93 yuan; the carbon emission cost is only 417.83 yuan, significantly lower than other systems. The above results show that, after considering the demand side response, the MEC comprehensive energy in the park can be more effectively optimized and the load distribution of the system can be improved, which is of great significance in power grid dispatching.
PubDate: 2023-05-19
- Selecting Green Suppliers by Considering the Internet of Things and CMCDM
Approach-
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Abstract: Selecting the suppliers in a green supply chain (GSC) improves supply chain capabilities by considering environmental policies. On the other hand, considering the development of technology and intelligence of the Internet of Things (IoT) and their help to meet goals better, it is essential to study them in this area. So, it is crucial to identify the influential factors of the IoT in selecting a green supplier and find its most important criteria for further monitoring and control. This paper aims to illustrate the ability of four different combinatorial multi-criteria decision-making (CMCDM) techniques in determining the best supplier in the rubber GSC. The suppliers are weighted using the fuzzy hierarchical analysis (FAHP) method, then ranked using four methods: VIKOR, TOPSIS, ELECTERE, and WASPAS. Then, their ranks are compared with each other. Eventually, Spearman’s rank correlation was examined to compare CMCDM methods. The results indicate that there is a similar ranking between all four CMCDM methods. Finally, it was found the second supplier is the best alternative for rubber companies looking for environmentally friendly suppliers. Also, FAHP-ELECTERE and FAHP-WASPAS methods have a high correlation with each other. The developed method can help decision-makers to make prompt decisions with less environmental pollution, which helps to achieve sustainable performance in the entire supply chain.
PubDate: 2023-05-13
- Non-dominated Sorting-Based Strategy for Optimizing the Mixture of
Initiators in Polyethylene Reactor-
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Abstract: Multi-objective optimization (MOO) of low-density polyethylene (LDPE) production in a tubular reactor is performed for three problems with three different objectives. For the first problem, the objective is maximization of productivity and minimization of cost of initiators. For the second problem, the objective is maximization of conversion and minimization of cost of initiators. While for the third problem, the objective is maximization of productivity, minimization of cost of initiators, and maximization of conversion. An inequality constraint on reactor temperature is also enforced to prevent the tubular reactor from a runaway condition. The non-dominated sorting–based strategies are utilized to tackle the optimization problem with Aspen simulator as model-based optimization for LDPE production in a tubular reactor. The strategies are non-dominated sorting genetic algorithm II (NSGA-II), non-dominated sorting grey wolf optimizer (NSGWO), and non-dominated sorting whale optimization algorithm (NSWOA). The inputs for MOO decision variables are mass flowrates of tert-butyl peroxypivalate (TBPPI), tert-butyl peroxyacetate (TBPA), tert-butyl 3,5,5 trimethyl-peroxyhexaonate (TBPIN), and tert-amyl peroxyacetate (TAPA). Performance matrices like hypervolume, spacing, and pure variability are examined to choose the most effective MOO approach. Findings showed that the NSGWO is the most effective MOO approach due to the discovered solution set providing the most precise, diverse, and appropriate in the homogeneity allocation points along the Pareto front (PF). The highest productivity, lowest cost of initiators, and highest conversion obtained by NSGWO are 549.369 Mil. RM/year, 7.5589 Mil. RM/year, and 31.685%, respectively.
PubDate: 2023-05-09
- Addressing Uncertainties in Planning Sustainable Systems Through
Multi-criteria Decision Analysis (MCDA)-
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PubDate: 2023-05-01
- An Application Method for the use of Neutrosophic Soft Mappings in
Decision-Making the Diagnosis of Covid-19 and Other Lung Diseases-
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Abstract: Covid-19 is an epidemic that has spread rapidly around the world and be direct damages the lung in recent years. Many researchers struggled for months trying to find a diagnosis and therapy for this epidemic. As a result of these studies, they have identified common of many symptoms of the epidemic disease with some lung diseases like flu, colds and even allergies. It can say that it is difficult to determine the exact disease type as lung diseases show similar symptoms. Because the elements of indeterminacy and falsehood are commonly ignored in practical assessments, it’s difficult to identify precision can’t anticipate the period of therapy and in the patient’s progress history. In order to after eliminate this uncertainty decide on the definitive diagnosis, a mathematical model was put forward by using neutrosophic soft set theory and function properties of this theory. These concepts are necessary and sufficient to accurately diagnose diseases by connecting with mathematical modeling. This study makes easier to establish a link between patients’ symptoms and therapy patterns. A table is created in fuzzy interval [0, 1] for put in order the type of disease among various lung diseases. Diagnosing the disease and finding the best therapy depends on the neutrosophic soft mapping. Finally the generalized neutrosophic soft mapping are utilized map to help predict the duration of therapy until the disease is cured.
PubDate: 2023-05-01
- GIS-Based Multi-criteria Approach Surface Irrigation Potential Assessment
for Ethiopian River Basin: in Case of Upper Awash River Basin-
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Abstract: Agriculture plays a significant role in the economy of Ethiopia. However, Ethiopian agriculture is vulnerable to rainfall, with minimal irrigation for agricultural production. The primary issue associated with rainfall-dependent agriculture is the instability and unreliability of rains. The main problems in this study area are that available water resources, potentially irrigable sites, and irrigation water demand for crops grown are not explicitly known. Therefore, the study’s main aim was to assess suitable lands in the upper Awash watershed for surface irrigation using a GIS-based multicriteria approach and computation of crop water requirement of dominant crops grown in the study area. The main essential factors used for land suitability assessment are land slope, soil physical characteristics, distance from the water source, and land use land cover. All the factors are weighted using ArcGIS to get the overall suitable area of the study area. The irrigation water demand of the dominant crops was assessed using metrological station data with the support of CROPWAT8.0 software. The dominant crops identified in the study area are potatoes and tomatoes. The study result revealed that the area is dominated mainly by moderately suitable land, covering 488,337.1 ha (48.4%). The highly suitable area covers 284,220.31 ha (28.17%), the marginally suitable area covers 147,221.205 (14.6%), and not a suitable area covers 89,121.23 ha (8.83%) for surface irrigation. The potentially suitable lands for surface irrigation in upper Awash subwatersheds, namely, Melka Kunture, Akaki, Mojo, and below Koka dam, are also identified. The finding signifies that gross irrigation water demand was more significant in almost all subwatersheds than the available streamflow. As a result, the government should work hard and develop various irrigation projects to use the upper Awash watershed’s potential irrigated lands by utilizing various irrigation water storage structures.
PubDate: 2023-05-01
- Effect of Green Supply Chain Practices on Sustainable Performance
Indicators: a Fuzzy MADM Approach-
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Abstract: Green supply chain practices (GSCPs) are initiatives to decrease the environmental effect of supply chain activities as identified by firms’ sustainable performance indicators (SPIs). This article aims to prioritise the organisational SPIs due to adopting the GSCPs. The literature yielded a total of 23 GSCPs and 20 SPIs. A hybrid framework based on fuzzy step-wise weight assessment ratio analysis (F-SWARA) and fuzzy weighted aggregated sum product assessment (F-WASPAS) is being developed to achieve the goal. According to the results, environmental rules and regulations, green organisational practices, supplier- and customer-related practices, green product and production practices, and green logistics practices are the GSCP’s main criteria in the order of its significance. According to the data, the top SPIs include better professional ethics, elimination/mitigation of environmental effects and societal dangers, cost savings on fines for environmental accidents, improved product quality with customer happiness, and increased productivity. The proposed method and methodology for assessing the GSCPs and SPIs simultaneously is new, and the data from an Indian manufacturing organisation also adds value to existing knowledge. These findings might be used for a range of goals, including external communications, internal improvements, and regulatory compliance.
PubDate: 2023-05-01
- Quadripartitioned Single-Valued Neutrosophic Properties and Their
Application to Factors Affecting Energy Prices-
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Abstract: The main idea of this study is the development of a quadripartitioned neutrosophic relations(properties)-based on decision-making method to recommend the most influential factor that affects energy prices in Colombia during pandemic. For supporting the results, we take some particular cities which are located in Colombia where prices of energy have been affecting before, during and after Covid-19 pandemic. The result provides evidence on the feasibility of the proposed method in recommending the influential factors that affect energy prices.
PubDate: 2023-05-01
- Analyzing the Application of the Sustainable Development Goals for Egypt
Using a Neutrosophic Goal Programming Approach-
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Abstract: Sustainable development necessitates the implementation of appropriate policies that integrate multiple competing objectives on economic, environmental, energy, and social criteria. Multi-criteria decision analysis with goal programming is a popular and widely used technique for studying decision problems with multiple competing objectives. Real-world situations frequently involve imprecise and incomplete information, making neutrosophic goal programming models the most appealing option. We presented a novel neutrosophic goal programming model that incorporates optimal resource allocation to simultaneously satisfy prospective goals on economic development, energy consumption, workforce, and greenhouse gas emission reduction by 2030, as applied to Egypt’s key economic sectors in this paper. We also compared the outcomes of fuzzy goal programming and neutrosophic goal programming. We show that neutrosophic goal programming approach is more accurate than fuzzy goal programming approach because it deals with incomplete and indeterminate information and has three independent degrees: truth membership degree, indeterminacy–membership degree, and falsity–membership degree. The presented model examines opportunities for improvement and the effort required to implement sustainable development plans. The model also provides valuable insights to decision makers for strategic planning as well as investment allocations for sustainable development. Numerical illustration is also provided for validation and application of the proposed model.
PubDate: 2023-05-01
- Analysing a GSCM Enabler–Based Model for Implementation of Its
Practices: a Pythagorean Fuzzy AHP and CoCoSo Approach-
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Abstract: Green supply chain management (GSCM) helps to improve the organizational performance and introduces environmental thinking into supply chain management. It is critical to comprehend the factors that promote GSCM acceptance. Hence, the research aims to develop and analyse a GSCM enabler–based model for implementation of its practices. A hybrid model based on Pythagorean fuzzy analytic hierarchy process (PFAHP) and Pythagorean fuzzy combined compromise solution (PFCoCoSo) is developed to study the influence of GSCM enablers on selected GSCM practices. The selected GSCM enablers are analysed, and its weights are determined using PFAHP. Using the GSCM enablers’ weights, GSCM practices are analysed using the PFCoCoSo method. This study identifies thirty-four GSCM enablers and twenty GSCM practices with rigorous literature review and discussion with selected experts. Environmental and legislation enablers (ELEs) and strategic managerial enablers (SMEs) are at the top among all GSCM enablers. The best practice to start GSCM is internal environmental management followed by formulating green policy and providing green training. The suggested model will assist industry practitioners in efficiently implementing GSCM practices taking help of GSCM enablers. The practitioners can focus on higher weight enablers to implement first. The ranking of GSCM practices helps the practitioners to develop the action plan in the initial phase of greening the current supply chain. This results in the reduction of failure chances and enhances the chance of successful GSCM adoption.
PubDate: 2023-05-01
- A Forecasting Study for Renewable Energy Resources Investments in Turkey:
TOPSIS-Based Linear Programming Model-
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Abstract: In this paper, a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)–based linear programming (LP) approach is developed for determining optimal quantities of renewable energy sources according to the source’s potential compared with other renewable energy alternatives. A combined model is established with the forecasting model, TOPSIS, and LP methods to determine optimal results. The developed decision support approach’s applicability is illustrated in this paper. The paper illustrates how renewable energy sources can be preferred to meet additional energy demand in the next five years in Turkey using the developed TOPSIS integrated LP model. For this objective, a time series analysis is applied to estimate production capacity for the constraints of the mathematical model. Then, a question is answered how much energy should be produced from which alternative for each year' A flexible structured mathematical model is developed to meet the necessary energy requirements in dynamic and variable economic systems. So, the decision-maker can assign different criteria weights in the TOPSIS model, which is integrated with LP, and obtain new optimal solutions related to requirements in the future.
PubDate: 2023-05-01
- Grey Relational Analysis–Based MADM Strategy Under Possibility
Environment and Its Application in the Identification of Most Important
Parameter Affecting Climate Change and the Impact of Urbanization on
Hydropower Plants-
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Abstract: This paper aims to establish the notion of Hamming distance under the possible environment and propose a multi-attribute decision-making (MADM) strategy based on grey relational analysis (GRA) under the Possibility environment. This study identified the most critical parameter or factors affected by climate change, urbanization, and machine failures. Furthermore, we validate the proposed MADM strategy by solving a real-world numerical example, namely, “identification of the most important parameters affecting climate change and the impact of urbanization on hydropower plants.”
PubDate: 2023-05-01
- Analysis of the Exergy, Economic, and Environmental Impacts and
Performance Enhancement of an Environmentally Friendly Solar Still with
Drop-wise Feeding-
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Abstract: This paper presents a novel approach for improving the performance of single slope solar still (SSSS) using drop-wise feed water supply. An ecofriendly single slope solar still is fabricated using readily available materials and experimentally investigated at R.E.C. (Rajkiya Engineering College), Azamgarh (latitude 25.7° N, longitude 82.9° E), Uttar Pradesh, India. In this study, drop-wise feed water supply has been chosen as a means of increasing the distillate yield of a solar still. Experiments are performed on two different design modifications of a single slope solar still: design 1 (a conventional solar still) and design 2 (drop-wise feeding of brackish water to the basin of the solar still). Drop-wise feeding of water to the solar still has been used to maintain a lower level of basin water, which improves the mass of distillate produced from the solar still. The performances of both designs of solar stills are compared theoretically and experimentally. In addition, designs 1 and 2 have also been investigated for energy, exergo-economic, and enviroeconomic impacts. The maximum distilled water produced is found to be 2.08 L/m2 and 2.79 L/m2 from designs 1 and 2, respectively. The daily energy efficiency is found to be 18.4% and 24.03% for designs 1 and 2, respectively. For designs 1 and 2, the cost of distilled water is determined to be Rs. 2.91/L, Rs. 2.19/L, with payback periods of 289 days and 218 days, respectively. The exergoeconomic parameters are computed to be 82 W-h/Rs and 138 W-h/Rs for designs 1 and 2, respectively. For designs 1 and 2, the CO2 (carbon dioxide) mitigation values are calculated to be 10.8 and 14.4 t of CO2 based on energy, and 0.29 and 0.51 t of CO2 based on exergy, respectively. The theoretical model of both designs shows acceptable agreement with the experimental results. Based on experimental analysis, design 2 is found to be more efficient and economical compared to design 1. The proposed design modification of drop-wise feeding to solar still produces potable water at a low cost, a high yield, and with environmental benefits. This study makes a valuable contribution to the development of sustainable and affordable water treatment technologies, particularly in regions with limited access to fresh water sources.
PubDate: 2023-04-24
- Development of a Methane Emission Prediction Tool (POMEP178) for Palm Oil
Mill Effluent Using Gaussian Process Regression-
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Abstract: Palm oil mill effluent (POME) contributes to 23.7% of the methane emissions in Malaysia. Development of a methane emission prediction tool by using machine learning (ML) enables the estimated volume of methane released to be determined. In this study, Gaussian Process Regression (GPR) along with its respective kernels was explored for the development of the prediction tool. Synthetic minority oversampling technique (SMOTE) was also implemented to study the effect of the training sample size used on the model validation. The GPR model was trained using synthetic data created from SMOTE, while the measure data from the plant was used to test the reliability of the trained model. The application of SMOTE was capable in producing high model validation performance (R2 = 0.98, RMSE = 0.133, MSE = 0.018 and MAE = 0.08) using the common squared exponential kernel GPR model. However, the Matern 5/2 and rational quadratic kernel GPR model had the best model validation performance (R2 = 0.98, RMSE = 0.131, MSE = 0.017 and MAE = 0.083). In terms of model testing performance, rational quadratic kernel had the best performance with R2 = 0.99, RMSE = 0.061, MSE = 0.0037 and MAE = 0.044. The results of this study indicate the prediction tool developed using SMOTE-based rational quadratic kernel GPR model can predict methane emissions with high accuracy. The methane emissions prediction tool developed is an alternative cost friendly and reliable option to existing methods.
PubDate: 2023-04-24
- Determination of Acid Dew Point Based on the Calculation of Thermodynamic
Equilibrium of Chemical Reactions of the Sulfuric Acid Formation Given the
Condensed State-
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Abstract: Acid dew point is the temperature at which the sulfuric acid vapor in flue gas begins to condense. Acid condensation can result in low-temperature corrosion that occurs on the convective heating surfaces. Low-temperature corrosion often leads to a disruption in the normal operation of heating surfaces, even failures, and a significant decrease in the efficiency of the entire boiler.
Authors used a method for calculating acid dew point of flue gases based on the conditions of thermodynamic equilibrium of chemical processes involving the transformation of compounds contained in flue gases, and the thermodynamic equilibrium of a multicomponent multiphase system, which is the flue gases. Based on the proposed methodology, a mathematical model has been developed. The authors developed a mathematical model of the boiler BKZ-75-39FB with the calculation of the abrasive wear of convective heating surfaces, the proportion of sulfur oxides bound by the fly ash of the fuel and by the sulfur-binding component, low-temperature corrosion rate for the purpose of a comprehensive assessment of the possibility of introducing this technical solution. The calculation of the acid dew point in the study is close to the actual ones.
PubDate: 2023-04-18
- A Multi-Attribute Decision-Making Model for Selecting Centralized or
Decentralized Municipal Solid Waste Management Facilities: a Study from
the Indian Perspective-
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Abstract: Centralized municipal colid waste (MSW) treatment facilities have disappointed stakeholders in India and other developing countries due to several premature failures. The operational risks behind these plants’ failure reveal significant loopholes in selecting a suitable approach. So, the dismal scenario advocates determining the appropriate indicators for choosing the centralized or decentralized type of facility and the priority of the indicators for easy decision-making. This present study decomposes this real-world problem into a multi-attribute decision-making (MADM) model with a novel methodology for determining the indicator’s weightage using the analytical hierarchy process (AHP) and fuzzy analytical hierarchy process (FAHP) methods. The rank-order correlation coefficient and Kruskal–Wallis H test predict that all these AHP and FAHP decision-making methods can equally perform the selection of the facility. However, the rank aggregation method determines the most effective set of weightages for decision-making. Furthermore, to validate the decision-making with the best collection of weightages, a feasibility analysis for selecting the suitable facility is carried out for two Indian cities. Thus, the outcome of the work will enable the appropriate selection of facilities in integrated municipal solid waste management systems (IMSWMS) for India and developing nations leading to the sustainable and efficient management of municipal solid waste.
PubDate: 2023-04-04
- Predicting Optimized Dissolution of Selected African Copperbelt
Copper-cobalt-bearing Ores by Means of Neural Network Prediction and
Response Surface Methodology Modeling-
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Abstract: While the uncertainty brought about by a varying feed mineralogy was taken into consideration, the paper investigated the modeling and prediction of the leaching behavior of complex copper-cobalt bearing ores, using an artificial neural network (ANN) with a backforward algorithm. The process optimization is further conducted using the response surface methodology (RSM) employing the Box-Behnken design (BBD). Seven (7) parameters were considered in a multiple linear regression according to the L12 screening plan (27) of Plackett–Burman. From the seven parameters, four including solid percentage (15, 27.5, 40%), time (45, 90, 135 min), particle size passing (53, 75, 105 µm), and Fe2+ ion concentration (2, 4, 6 g/L) are modeled with L27(34) BBD. With a composite desirability of 0.94, leaching yields of 93.46% Cu and 89.43% Co were obtained. The neural network algorithm used is the BFGS (Broyden, Fletcher, Goldfarb and Shanno) algorithm multilayer perceptron with the hyperbolic tangent activation function for the hidden layer and a linear activation function for the neural output. The Multilayer perceptron {4–7-1} structure was chosen as a suitable arrangement for Cu leaching. Comparing the predicted values and those obtained experimentally resulted with a correlation coefficient of 0.9552 for the data trained in the artificial neural network and 0.8742 for the data obtained with the response surface methodology. The synergy of these 2 techniques shows that the prediction can be achieved by means of the ANN giving the values of the root mean square errors (RMSE) of 0.0115, 0.00624, 0.0229, respectively, for the training, testing and validation sets for copper recovery while the correlational study between variables could be done through the RSM. The above includes only the 95% confidence interval while the remaining 5% would be uncertain. The above results and conclusion are accompanied by the relative uncertainty as the ore mineralogy varies. The combination of the synergistic use of ANN and RSM with the sensitivity analysis has approached the process to the physics of the Multi-criteria decision-making. Graphical 
PubDate: 2023-03-04
DOI: 10.1007/s41660-023-00312-3
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