Search Results - (( data evaluation method algorithm ) OR ( parameter optimization swarm algorithm ))

Neural network approach for global solar irradiance prediction at extremely short-time-intervals using particle swarm optimization algorithm by Aljanad A., Tan N.M.L., Agelidis V.G., Shareef H.

Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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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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An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali, M Osman, Tokhi

“…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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Comparison of several improved versions of particle swarm optimizer algorithm for parameter estimation of squirrel-cage induction motors / Mohammad Yazdani-Asrami, Mehran Taghipour Gorjikolaie and S.... by Gorjikolaie, Mehran Taghipour, Gholamian, S. Asghar

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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…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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Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

“…The proposed framework and methods are evaluated using the state-of-the-art datasets from the NASA metric data repository. …”
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Optimization and Decomposition Methods in Network Traffic Prediction Model: A Review and Discussion by Jinmei Shi, Yu-Beng Leau, Kun Li, Yong, Jin Park, Zhiwei Yan

“…The comprehensive review reveals that PSO and VMD are the most suitable optimization algorithm and decomposition technology for network traffic prediction modeling…”
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Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System by Abd Rahman, Azira

“…This research aimed to develop a Predictive Functional Control using Reduced-Order Observer (PFC-ROO) to reduce the complexity of the pneumatic system. An optimization technique will be implemented in this project using Particle Swarm Optimization (PSO) algorithm. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem by Wong, Jerng Foong

“…It is also used extensively in experiments to test the performances of metaheuristic algorithms and their hybrids. For example, Tabu Search (TS) has been successfully hybridized with other techniques, including particle swarm optimization (PSO) algorithm and the two-stage TS algorithm to solve MKP. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

“…In this regard, a Local Sensitivity Analysis, Segment Particle Swarm Optimization (Se-PSO) algorithm, and the Enhanced Segment Particle Swarm Optimization (ESe-PSO) algorithm was adapted and proposed to estimate the parameters. …”
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Development of a two-level trade credit model with shortage for deteriorating products using hybrid metaheuristic algorithm by Molamohamadi, Zohreh

“…A hybrid metaheuristic algorithm which combines Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm, is then developed to solve the established models. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO by Naffouti, S.E., Aouissaoui, I., Fougerolle, Y., Sakly, A., Meriaudeau, F.

“…The algorithm is evaluated by its capability to differentiate between the salient feature points and to match efficiently between similar geometric structures for the same shape in different poses. © 2016 IEEE.…”
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OPTIMIZATION OF PID CONTROLLER PARAMETERS USING ARTIFICIAL FISH SWARM ALGORITHM by SOOMRO, WAFA ALI SOOMRO

“…This Final Year Project is preceded on the topic named “The Optimization of PID Control Parameters Using Artificial Fish Swarm Algorithm”. …”
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

“…The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

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Application of Particle Swarm Optimization in Optimizing Stereo Matching Algorithm’s Parameters for Star Fruit Inspection System by Nasroddin, Saidatul Nizan, Mohd Mokji, Musa, Tan, Kok, Zainal Abidin, Amar Faiz, Amirulah, Rahman, Nordin, Nur Anis, Hasim, Saipol Hadi, Zakaria, Hamzah, Hassan, Jefery, Jaafar, Hazriq Izzuan, Khairuddin, Osman

“…This paper reports the finding of the experimentation of the Particle Swarm Optimization in optimizing the stereo matching algorithm’s parameters for the star fruit inspection system. …”
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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