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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

“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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Verification of correctness properties for aggregation behavior of swarm robotics system using spin model checker / Siti Shafinaz Ali by Ali, Siti Shafinaz

“…This research work focused on a developed swarm algorithm aimed at swarm aggregation. …”
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Verification correctness properties for aggregation behavior of swarm robotics system using SPIN model checker / Siti Shafinaz Ali by Ali, Siti Shafinaz

“…This research work focused on a developed swarm algorithm aimed at swarm aggregation. …”
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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

“…Thus, this research aimed to estimate large-scale kinetic parameters of the main metabolic pathway of the E. coli model. 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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A microscopic swarm model simulation and fractal approach towards swarm agent behaviour by Widyarto, Setyawan, Abd. Latiff, Muhammad Shafie

“…A physical based microscopic agent simulation model has been developed. The developed microscopic agent simulation model is a physical force based model similar to the social force model with forward and repulsion forces as the main force driver. …”
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CO 2 emission model development employing particle swarm optimized Least squared SVR (PSO-LSSVR) hybrid algorithm by Rosdiazli bin Ibrahim, Vijanth Sagayan A/L Asirvadam

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CO2 Emission Model Development Employing Particle Swarm Optimized - Least Squared SVR (PSO-LSSVR) Hybrid Algorithm by Rosdiazli bin Ibrahim, Vijanth Sagayan A/L Asirvadam

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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment by M. F., Masrom, N. M. A., Ghani, M. O., Tokhi

“…This paper presents investigations into the development of an interval type-2 fuzzy logic control (IT2FLC) mechanism integrated with particle swarm optimization and spiral dynamic algorithm. …”
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A hybrid bat�swarm algorithm for optimizing dam and reservoir operation by Yaseen Z.M., Allawi M.F., Karami H., Ehteram M., Farzin S., Ahmed A.N., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., El-Shafie A.

Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

“…In order to supply sufficient test problems that cover a range of problem difficulties, a tuneable test problem generator is developed. Statistical tests on the algorithms' performance indicates that the proposed MODPSO algorithm presents significant improvement in terms of larger nondominated solution numbers in Pare't o optimal, compared to comparable algorithms including GA based algorithms in both single-model and mixedmodel ASP and ALB problems. …”
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Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso by Mohammed Adam Kunna, Azrag, Jasni Mohamad, Zain, Tuty Asmawaty, Abdul Kadir, Marina, Yusoff, Jaber, Aqeel Sakhy, Abdlrhman, Hybat Salih Mohamed, Ahmed, Yasmeen Hafiz Zaki, Husain, Mohamed Saad Bala

“…In this regard, the result of the ESe-PSO algorithm achieved superior accuracy compared with the Segment Particle Swarm Optimization (Se-PSO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) algorithms. …”
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Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin by Che Wan Samsudin, Che Wan Sufia

“…The development of a predictive model for condominium prices using the Particle Swarm Optimization-Random Forest approach is the key focus of this research project. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

“…The multistate model is then implemented in PSO and GSA. As a consequence, multi-state particle swarm optimization (MSPSO) and multi-state gravitational search algorithm (MSGSA) are developed. …”
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Route Optimization System by Zulkifli, Abdul Hayy

“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation by Yaseen, Zaher Mundher, Allawi, Mohammed Falah, Karami, Hojat, Ehteram, Mohammad, Farzin, Saeed, Ahmed, Ali Najah, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

“…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques by Lipu M.S.H., Hussain A., Saad M.H.M., Hannan M.A.