Search Results - (( variable optimization model algorithm ) OR ( loading optimization based algorithm ))
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”
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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“…In this project, an Artificial Neural Network (ANN) trained by the Invasive Weed Optimization (IWO) learning algorithm is proposed for short term load forecasting (STLF) model. …”
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Student Project -
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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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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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Optimizing energy and reserve minimization in a sustainable microgrid with electric vehicle integration: dynamic and adjustable manta ray foraging algorithm
Published 2023“…The DAMRF algorithm harnesses the inherent flexibility of EVs as controllable loads and develops a comprehensive dispatch model for a large-scale EV response. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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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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Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration
Published 2025“…The backward reduction method (BRM) is then applied to streamline the number of generated scenarios, reducing computational efforts. To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”
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Capacity Planning For Mixed-Load Tester Under Demand And Testing Time Uncertainty
Published 2018“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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Thesis -
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To develop an efficient variable speed compressor motor system
Published 2007“…To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. …”
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…The most important stages in a process were modeling and optimization to improve a system and increase the efficiency of the process without increasing the cost. …”
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An intelligent hybrid short-term load forecasting model for smart power grids
Published 2017“…In this model, a global best particle swarm optimization (GPSO) algorithm is applied as a new training technique to enhance the performance of ANN prediction. …”
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Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption
Published 2013“…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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Conference or Workshop Item -
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Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine
Published 2009“…C. The model can also be used for performance optimization studies.…”
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Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology
Published 2025“…A hybrid optimization algorithm addresses the proposed objectives, combining the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to minimize the three distinct objective functions concurrently. …”
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