Search Results - (( processes optimization model algorithm ) OR ( variable extraction method algorithm ))
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1
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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2
Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphso...
Published 2022“…Extraction of the photovoltaic (PV) model parameters is critical for forecasting these systems’ energy output. …”
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3
Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…A multi-objective feature selection approach comprises of multi-objective binary-valued backtracking search algorithm (MOBBSA) as an efficient evolutionary search algorithm and ANFIS method is developed in this paper to extract the most influential subsets of input variables with maximum relevancy and minimum redundancy. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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5
Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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6
Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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7
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…Therefore, this study explores how to model reconfigurable manufacturing activities in an optimization perspective and how to develop and select appropriate non-conventional optimization techniques for reconfigurable process planning.In this study, a new approach to modeling Manufacturing Process Planning Optimization (MPPO) was developed by extending the concept of manufacturing optimization through a decoupled optimization method. …”
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Adaptable algorithms for performance optimization of dynamic batch manufacturing processes
Published 2018“…Traditionally, a fixed temperature profile has been identified and assumed as ‘nominal optimized’ for manufacturers to follow. Whether the process is fully optimized under inconsistent internal heat liberation, external environmental variations, model mismatches and process uncertainties remains as a challenging topic. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
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Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm
Published 2013“…Finally, non-dominated sorting genetic algorithm-II as evolutionary optimization approach was used for multi-objective optimization of the micro-end milling process. …”
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12
Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm
Published 2023“…Costs; Efficiency; Routing algorithms; Scheduling; Solid wastes; Vehicle routing; Capacitated vehicle routing problem; Modified particle swarm optimization; Optimized models; Route optimization; Solid waste collection; Threshold waste level; Travel distance; Waste collection; Particle swarm optimization (PSO); fuel; algorithm; numerical model; optimization; routing; solid waste; transport vehicle; waste disposal; algorithm; Article; capacitated vehicle routing problem model; controlled study; cost; decision making; environmental impact; motor vehicle; nonbiological model; particle swarm optimization algorithm; priority journal; problem solving; process optimization; socioeconomics; solid waste management; travel; validation process; economics; solid waste; waste management; Algorithms; Costs and Cost Analysis; Solid Waste; Waste Management…”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Modeling and Prediction of The Mechanical Properties of Feedstock by Cooling-Slope Casting Process using MOJaya Algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani
Published 2021“…In model validation, to quantify accuracy by approving the informational collection, Ant Colony Optimization Algorithm was used and it was compared with the J48 algorithm. …”
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Student Project -
16
Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches
Published 2018“…The established extrusion force model was then taken as the fitness function. Subsequently, the analytical approach and metaheuristic algorithms, specifically the particle swarm optimization, cuckoo search algorithm (CSA) and flower pollination algorithm, were applied to optimize the extrusion process parameters. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. …”
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Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm
Published 2013“…The model has significant benefits in application to fabrication processes.…”
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Optimization of multi-holes drilling toolpath using tiki-taka algorithm
Published 2024“…The study aims to model the MDMT toolpath using the Traveling Salesman Problem (TSP) concept, apply TTA to optimize this model, and validate the model and algorithm through machining experiments on this problem. …”
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Modeling and Prediction of the mechanical properties of feedstock by cooling-slope casting process using MOJaya algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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