Search Results - (( waste ((maximization algorithm) OR (optimisation algorithm)) ) OR ( waste selection algorithm ))
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Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm
Published 2025“…This study proposed the application of the Artificial Bee Colony (ABC) algorithm to address the Capacitated Vehicle Routing Problem (CVRP) in a real-world waste collection scenario. …”
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Student Project -
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Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation
Published 2020“…Through the implementation of selected multi-objective genetic algorithm, it was able to produce the pareto front for optimising both nitrogen concentration and the extension rate of the mycelium. …”
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Conference or Workshop Item -
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DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management
Published 2024“…The M5P algorithm, adept at profit estimation, establishes correlations between MSW weight and profitability, while the J48 algorithm offers recommendations for suitable waste conversion technologies based on profit potential. …”
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Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm
Published 2017“…The EANN used a modified activation function to meet the optimisation requirement. To evaluate the EANN model, 19 samples of experimental data from Zainol on the regression modelling of biogas production from banana stem waste were selected. …”
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Thesis -
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Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari
Published 2021“…Sugeno fuzzy inference system (FIS) algorithm was used to model influent parameter, and the FIS parameters were adjusted by ANFIS, integrated Genetic algorithms, GA-FIS, and integrated particle swarm optimisation, PSO-FIS, algorithms. …”
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Thesis -
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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis
Published 2017“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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Thesis -
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…The Voting regression, which leverages the collective predictive power of multiple models, exhibits superior performance in comparison to individual algorithms. Feature selection methods play a crucial role in identifying the variables that have a significant impact on project costs. …”
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Article -
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Exothermic batch process optimisation via multivariable genetic algorithm
Published 2012“…However, this reference profile is unable to limit the waste production effectively. Therefore, multivariable genetic algorithm (MGA) is proposed in this work to optimise the productivity of the process without referring to the predetermined reference profile. …”
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Proceedings -
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Genetic algorithm for control and optimisation of exothermic batch process
Published 2013“…As such, another approach, GA is proposed to optimise the productivity without referring to a predetermined profile, namely genetic algorithm optimiser (GAO). …”
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Thesis -
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Modelling Of Biogas Production From Banana Stem Waste With Neural Networks Learning Strategies To Optimse The Production
Published 2017“…In recent years, intelligence computation is applied to design a better process model and optimised biogas yield. This paper presents a comparative study of several neural networks learning (back-propagation, resilient propagation, Lavenberg-Marquardt and particle swarm optimisation) algorithms for process modelling and optimisation and its relation with the optimisation result. …”
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Article -
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Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)...
Published 2019“…This new framework will be able to provide range of possible recall rate from minimum to maximum, to identify which classifier algorithm performs the best for given dataset. The selected model can be implemented into actual manufacturing flow to screen predicted bad die for maximum cost scrapping avoidance and capacity savings.…”
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Mathematical Modelling and Optimisation of Hydrogen Production from Photo-Fermentation in Microbial Electrolysis Cell using Sago Waste with Neural Network Algorithm
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Final Year Project Report / IMRAD -
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin
Published 2021“…The computation time complexity of the Q-Learning-based test coverage algorithm was also analyzed. The results showed that time complexity was reduced significantly from …”
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A hybrid P-graph and WEKA approach in decision-making: waste conversion technologies selection
Published 2022“…The focus of user interface for selection of waste conversion technologies. As a result, the model can be used to determine the best municipal solid waste conversion technology.…”
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations
Published 2022“…Biodiesel production often results in the production of a significant amount of waste glycerol. Through various technological processes, waste glycerol can be sustainably utilized for the production of value-added products such as hydrogen. …”
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A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions
Published 2023“…This research focuses on two solid waste management (SWM) problems, particularly the landfill site selection problem (LSSP) and the waste collection vehicle routing problem (WCVRP). …”
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Thesis -
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2023“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”
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