Search Results - (( swarm optimization method algorithm ) OR ( data reduction methods algorithm ))

Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

“…Therefore, it can be solved by using population-based techniques such as Genetic Algorithm and Particle Swarm Optimization. This paper proposes the integration of feature reduction and data reduction for fuzzy modeling using Cooperative Binary Particle Swarm Optimization (CBPSO). …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

“…In the experiment, we conducted an evaluation of the effectiveness and efficiency of four nature-inspired binary algorithms for optimization namely Binary Particle Swarm Optimization (BPSO), Binary Grey Wolf Optimization algorithm (BGWO), Binary Differential Evolution algorithm (BDE), and Binary Salp Swarm algorithm (BSS) - in the context of human activity recognition (HAR). …”
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Optimal configuration of wind farms in radial distribution system using particle swarm optimization technique by Kumar, M., Das, B., Nallagownden, P., Elamvazuthi, I., Khan, S.A.

“…The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. …”
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Optimal configuration of wind farms in radial distribution system using particle swarm optimization technique by Kumar, M., Das, B., Nallagownden, P., Elamvazuthi, I., Khan, S.A.

“…The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

“…PSO is a swarm-based search algorithm perform a stochastic search to explore the search space. …”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

“…Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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Modeling Of Electrical Distribution Networks With Particle Swarm Optimization Technique For The Improvement Of Voltage Profile And Loss Reduction by Shahad, Falih Khlaif

“…Installation of capacitors before and after optimization was compared based on voltage profile and reduction of power losses. …”
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Particle swarm optimization algorithm to enhance the roughness of thin film in tin coatings by Jamil Alsayaydeh, Jamil Abedalrahim, Zainon, Maslan, Mohammad Alshannaq, Osama Saleh, Hammouda, Montaser B A, Ali, Mohanad Faeq, Alkhashaab, Mohammed Abdul Razaq, Mohamad Jaya, Abdul Syukor

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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

“…To further enhance the scheduling system, future work should focus on integrating additional optimization techniques such as Particle Swarm Optimization or Simulated Annealing to refine scheduling accuracy. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

“…Given the NP-Hard nature of the three models proposed in this thesis, two metaheuristic algorithms have been developed. A hybrid Particle Swarm Optimization-Bacterial Foraging Algorithm is developed for solving the single objective LIRP model. …”
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Feature and Instance selection via cooperative PSO by Syed Ahmad, Sharifah Sakinah

“…The reduction method contains two main techniques: feature selection and instance selection, which are usually applied individually. …”
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Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters by Abdul Syukor, Mohamad Jaya, Mu*ath Ibrahim, Mohammad Jarrah, Mohd Asyadi Azam, Mohd Abid, Mohd Razali, Muhamad

“…Optimization of thin film coating parameters is important in identifying the required output.Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties.The aim of this study is to identify optimal PVD coating process parameters.Three process parameters were selected,namely nitrogen gas pressure (N2),argon gas pressure (Ar),and Turntable Speed (TT),while thin film grain size of titanium nitrite (TiN) was selected as an output response.Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment.In this paper,to obtain a proper output result,an approach in modeling surface grain size of Titanium Nitrite (TiN)coating using Response Surface Method (RSM) has been implemented. Additionally,analysis of variance (ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters,genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

“…The three objective functions, i.e., power loss reduction, voltage stability improvement, and voltage deviation minimization are optimized using advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization method. …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array by Alkhafaji, Falih Salih

“…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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New optimization technique to design the core of three-phase transformer by Alyozbaky, Omar Sh., Ab Kadir, Mohd Zainal Abidin, Izadi, Mahdi, Gomes, Chandima, Azis, Norhafiz, Mohd Isa, Maryam

“…In this study, an intelligent algorithm employing particle swarm optimization (PSO) has been used to get the optimum T-joint design of a core in a three-phase transformer. …”
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Improved particle swarm optimization by fast annealing algorithm by Bashath, Samar, Ismail, Amelia Ritahani

“…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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