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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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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control by Ahmad, Mohd Ashraf, Izci, Davut, Ekinci, Serdar, Mohd Tumari, Mohd Zaidi

“…The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. …”
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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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Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm by Mohd Tumari, Mohd Zaidi Mohd, Mustapha, Nik Mohd Zaitul Akmal, Ahmad, Mohd Ashraf, Saat, Shahrizal, Ghazali, Mohd Riduwan

“…Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. …”
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Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Nik Mohd Zaitul Akmal, Mustapha, Shahrizal, Saat

“…Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. …”
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Data-driven fractional-order PID controller tuning for liquid slosh suppression using marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali, Shahrizal, Saat

“…In response, this study introduces a data-driven fractional-order PID (FOPID) controller designed using the Marine Predators Algorithm (MPA) for suppressing liquid slosh. …”
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A Wavelet-Based Approach For The Analytical Solutions Of Fractional Differential Equations And The Numerical Solutions Of Fractional Integral Equations by Loong, Marcus Ong Wei

“…Following the rise of fractional-order models and consequently, their fractional governing equations, new analytical and numerical methods have been developed and studied extensively. …”
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Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

“…The second approach relies on Chelyshkov basis functions for approximation and utilizes the extreme machine learning algorithm for weight determination, achieving high accuracy and low computational time. …”
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A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato... by Alsa’Di, Kawthar, Nik Long, Nik Mohd Asri

“…This technique uses the Adaptive Moment Estimation Method (Adam) as an optimization algorithm with feed-forward deep learning to minimize the error function and training the model using five layers with different activation functions. …”
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Quaternion-based dynamic algorithm for random generation of solid 4D cylindrical curves in RVE modeling by Hamat, Sanusi, Ishak, Mohamad Ridzwan, Kelly, Piaras, Salit, Mohd Sapuan, Yidris, Noorfaizal, Ali, Syamir Alihan Showkat, Hussin, Mohd Sabri, Mohd Dawi, Mohd Syedi Imran

“…Micro-scale RVEs were successfully generated across fiber volume fractions up to 50 %, validated through second‐order orientation tensor analysis and statistical evaluations using Probability Density Functions (PDFs) and Cumulative Distribution Functions (CDFs). …”
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Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column by Maan, Normah

“…A series of algorithms in solving the inverse problem were then developed corresponding to the forward models. …”
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Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions by Alsa’di, Kawthar, Nik Long, Nik Mohd Asri, Senu, Norazak, Eshkuvatov, Z.K.

“…A hybrid technique, combining a polynomial neural network (PNN) with an extreme learning machine algorithm without using any activation functions, is developed. …”
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Approximation techniques by Bingi, K., Ibrahim, R., Karsiti, M.N., Hassan, S.M., Harindran, V.R.

“…Hence, for achieving the approximated integer-order transfer function of the fractional-order system or controller, a novel curve fitting based approximation techniques for fractional-order differentiator or integrator are developed. …”
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Predictive analytics of Junctionless Double Gate Strained MOSFET using genetic algorithm with doe-based grey relational analysis by Salehuddin, Fauziyah, Kaharudin, Khairil Ezwan, Ahmad Jalaludin, Nabilah, Arith, Faiz, Mohd Zain, Anis Suhaila, Ahmad, Ibrahim, Md Junos@Yunus, Siti Aisah

“…Finally, the genetic algorithm is utilized to predict the optimum level of design parameters based on the derived objective function. …”
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

“…Therefore, the main interest of the cancer trials is in determining the fraction of cured patients so as to obtain the trends in the survival of cancer patients. …”
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PREDICTIVE ANALYTICS OF JUNCTIONLESS DOUBLE GATE STRAINED MOSFET USING GENETIC ALGORITHM WITH DOE-BASED GREY RELATIONAL ANALYSIS by Kaharudin K.E., Salehuddin F., Jalaludin N.A., Arith F., Zain A.S.M., Ahmad I., Junos S.A.M.

“…Finally, the genetic algorithm is utilized to predict the optimum level of design parameters based on the derived objective function. …”

Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations by Shloof, Aml Melad Asan

“…In the second part of the thesis, we developed the Hilfer fractal-fractional derivative definition. …”
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Multi-Objective Optimization of Solar Powered Irrigation System by Using Genetic Algorithm by Mohd Tholaat, Muhammad Ali Husaini

“…Initial range of [1; 2] and crossover fraction of 1.0 have majorly contributed to the optimal search parameters. …”
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