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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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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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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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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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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…4.457, and KGE = 0.737) compared to other models. Furthermore, the utilization of FA and ABC optimization techniques facilitated the optimization of the ANN model parameters. …”
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Load dispatch optimization of open cycle industrial gas turbine plant incorporating operational, maintenance and environmental parameters
Published 2006“…The objective of this work is to develop a multi-objective optimization model and optimization algorithm for load dispatching optimization of open cycle gas turbine plant that not only consider operational parameters, but also incorporates maintenance and environmental parameters. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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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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Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm
Published 2018“…The main goal of this research work is to propose the novel practical models to predict the BI through particle swarm optimization (PSO) and imperialism competitive algorithm (ICA). …”
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Hybrid ant colony optimization algorithm for container loading problem
Published 2012“…Preliminary computational experiments were conducted on a subset of benchmark data sets as to find the appropriate parameters setting for the developed HACO. The proposed algorithm is tested on two standard benchmark data sets to evaluate the performance and to determine the effectiveness of the algorithm. …”
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Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid
Published 2015“…Step input load deviation is injected to the system at designated location and the optimization of ramp rate, speed regulation and the IλDμ parameters are carried out. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Due to the effective attraction-repulsion mechanism of electromagnetic-like (EM) algorithm and reliable exploration and exploitation phases of differential evolution (DE), these two methods were used to determine parameters of the single diode PV model and finding optimal sizing of the SAPV system. …”
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…The post-islanding frequency stability is maintained by optimizing the Load Frequency Control‘s parameters. …”
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Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model
Published 2024“…Total cost minimization, peak load shifting, and residents� thermal comfort satisfaction are combined and considered in the optimal scheduling algorithm. …”
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…The PSO algorithm is used to optimize the loop-shaping step (subject to QFT constraints), which is performed manually in the standard QFT control design. …”
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