Search Results - (( developing demand function algorithm ) OR ( data using optimization algorithm ))
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan
Published 2025“…The aim of this study is to optimize the demand response of solar energy generation using Genetic Algorithm (GA) to minimize the daily yield loss caused by load shedding. …”
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Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions
Published 2024“…The proposed approach's effectiveness is evaluated within an IEEE 14-bus configuration with five microgrids (MGs) integrated with RESs using real load data from Perlis, Malaysia. The BPSO optimization technique offers an exceptional binary fitness function to find the optimal cell, utilizing real data such as solar radiation, wind speed, battery charging/discharging, fuel conditions, and demand. …”
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Development Of Generative Computer-Aided Process Planning System For Lathe Machining
Published 2019“…These functions always create irregular data descriptions in current CAD and CAM system supply and demand. …”
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Moth Flame Optimization Algorithm including Renewable Energy for Minimization of Generation & Emission Costs in Optimal Power Flow
Published 2022“…This problem must be overcome to achieve the goals while keeping the system stable. Moth Flame Optimization (MFO), a recently developed metaheuristic algorithm, will be used to solve objective functions of the OPF issue for combined cost and emission reduction in IEEE 57-bus systems with thermal and stochastic wind-solar-small hydropower producing systems. …”
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Novel reservoir system simulation procedure for gap minimization between water supply and demand
Published 2019“…In this research, an optimization algorithm, namely, the shark machine learning algorithm (SMLA) that has high inertia for obtaining its targets, is proposed that mimics the natural shark process. …”
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Optimal Power Flow of power systems using Harris Hawks Optimization and Salp Swarm Algorithm
Published 2021“…This thesis has proposed recently developed Harris Hawks Optimization (HHO) and Salp Swarm Algorithm (SSA) to solve single- and multi-objective OPF problems considering fuel cost, power loss and environment emission. …”
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Green network planning and operational power consumption optimization in LTE-A using artificial intelligence
Published 2015“…A cascaded multi-objective genetic algorithm network optimization (CMOGANO) is developed to optimize the network number of base station, their location and configuration in the first stage to provide full coverage. …”
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Controller placement problem in the optimization of 5G based SDN and NFV architecture
Published 2021“…A heuristic called dynamic mapping and multi-stage CPP algorithm (DMMCPP) was developed to solve CPP as resource allocation in a distributed 5G-SDN-NFV-based network. …”
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Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung
Published 2023Conference Paper -
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Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System
Published 2020“…An optimization technique will be implemented in this project using Particle Swarm Optimization (PSO) algorithm. …”
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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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Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm
Published 2015“…This includes the use of an artificial neural network (ANN) based predictive control strategy and differential evolution (DE) optimization algorithm to determines the optimal control signal, uk (liquid droplet size, dD) by minimizing the cost function such that the output is set below the allowable PM concentration. …”
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Proceeding Paper -
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…However, the evaluation function used in the AI is developed based on historical traffic data. …”
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A decision support system for improving forecast using genetic algorithm and tabu search
Published 2008“…and their combinations using trial and error method is time consuming. Hence, a good optimization technique is required to select the best parameter value to minimize the fitness function. …”
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Multifunctional optimized group method data handling for software effort estimation
Published 2022“…Nevertheless, finding the best effort estimation model with good accuracy is hard to serve this purpose. Group Method of Data Handling (GMDH) algorithms have been widely used for modelling and identifying complex systems and potentially applied in software effort estimation. …”
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