Search Results - (( data optimization model algorithm ) OR ( variable operation using algorithm ))
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Thesis -
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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
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Optimum Power Production of Small Hydropower Plant (SHP) Using Firefly Algorithm (FA) in Himreen Lake Dam (HLD), Eastern Iraq
Published 2017“…This study focuses on the improvement of optimization model by applying particle swarm optimization and firefly algorithm methods in order to get a stable power production utility at its maximum level. …”
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Optimal Long-Term Hydro Generation Scheduling of Small Hydropower Plant (SHP) using Metaheuristic Algorithm in Himreen Lake Dam
Published 2017“…This study focuses on the improvement of optimization model by applying particle swarm optimization and firefly algorithm methods to get a stable power production utility at its maximum level. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025Subjects:Article -
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…In the FPSO method, the local search is performed through the modified light intensity attraction step with PSO operator. Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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Thesis -
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Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong
Published 2013“…Input parameters are optimized using HEA to weed out insignificant input for predicting Chlorophyta abundance. …”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization
Published 2025“…In addition to that, a Genetic Algorithm (GA)-based optimization system and Simulated Annealing optimization Algorithm (SAA) were proposed to determine an economical solution for decreasing the cost of the NG system depending on its operational constraints. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Thesis -
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DRIFT ANALYSIS ON NEURAL NETWORK MODEL OF HEAT EXCHANGER FOULING
Published 2008“…This paper proposes the use of information criteria for tracking the model prediction accuracy and provides an algorithm for retraining the model. …”
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Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine
Published 2009“…Real operation data collected in 10 seconds interval are used for training as well as validation of the model. …”
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Multi-Objective Optimization of Minimum Quantity Lubrication in end Milling of Aluminum Alloy AA6061T6
Published 2015“…Analysis of variance at a 95% confidence level is implemented to identify the most significant input variables on the CNC end milling process. Optimization of the responses is done using a multi-objective genetic algorithm. …”
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Optimization of emulsion polymerization of styrene and methyl methacrylate (MMA)
Published 2013“…Using gPROMS, the system analyzed the data, created models, developed algorithms, manipulated and plotted based on the functions and data. …”
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Undergraduates Project Papers -
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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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Thesis -
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Multiobjective Fuzzy Mixed Assembly Line Sequencing Optimization Model
Published 2014“…A genetic algorithm (GA) approach is used to solve this problem, in which trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data.…”
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Profit Optimization of a Refrigerated Gas Plant
Published 2007“…To widen its profit margin, the plant needs to operate more efficiently. This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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Profit Optimization of a Refrigerated Gas Plant
Published 2007“…To widen its profit margin, the plant needs to operate more efficiently. This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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