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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir

“…In this paper, a new variant of Manta Ray Foraging Optimization (MRFO) algorithm is introduced to deal with real parameter constrained optimization problem. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

“…The transformation results in an equivalent mixed discrete optimization problem. The transformed problemis then decomposed into a bi-level optimization problem, which is solved using a combination of an efficient discrete filled function method identified earlier and a computational optimal control technique based on the concept of control parameterization. …”
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Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty by Ali, Hazem Ibrahim, Mohd Noor, Samsul Bahari, Bashi, Sinan Mahmod, Marhaban, Mohammad Hamiruce

“…This paper presents a new method for tuning the weighing functions to design an H∞ controller. Based on a particle swarm optimization (PSO) algorithm the, weighting functions are tuned. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

Implementation of Symmetric Rank-One Methods for Unconstrained Optimization by Khiyaban, Farzin Modarres

“…We then examine a new scaled memoryless SR1 method based on modied secant equation for solving large-scale unconstrained optimization problems. …”
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Catalytic conversion of methane and carbon dioxide in conventional fixed bed and dielectric barrier discharge plasma reactors by Istadi, Istadi

“…Moreover, the operating parameters, such as the CO2/CH4 feed ratio and reactor temperature, and the catalyst compositions, such as wt% CaO and wt% MnO, were optimized by using Weighted Sum of Squared Objective Functions algorithm. …”
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A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

“…Machine learning algorithms are iteration based algorithms, as the new knowledge is based on the previous predicted /calculated knowledge which helps to decrease errors in order to increase efficiency. …”
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Improved Segregated Advancement (I-SA): a new method for solving full triangular fuzzy transportation problems by Muhammad Sam’An, Muhammad Sam’An, Yosza Dasril, Yosza Dasril, Chandrasekar Ramasamy, Chandrasekar Ramasamy, Bujang, Nazarudin, Yahya, Nur Ifriza

“…Therefore, we proposed the improvement based on the combination of total ratio cost matrix and total difference method by column without using classical ranking functions. …”
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Improved Segregated Advancement (I-SA): a new method for solving full triangular fuzzy transportation problems by Muhammad Sam’An, Muhammad Sam’An, Yosza Dasril, Yosza Dasril, Chandrasekar Ramasamy, Chandrasekar Ramasamy, Nazarudin Bujang, Nazarudin Bujang, Yahya Nur Ifriza, Yahya Nur Ifriza

“…Therefore, we proposed the improvement based on the combination of total ratio cost matrix and total difference method by column without using classical ranking functions. …”
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Improved Segregated Advancement (I-SA): a new method for solving full triangular fuzzy transportation problems by Muhammad Sam’An, Muhammad Sam’An, Yosza Dasril, Yosza Dasril, Chandrasekar Ramasamy, Chandrasekar Ramasamy, Nazarudin Bujang, Nazarudin Bujang, Yahya Nur Ifriza, Yahya Nur Ifriza

“…Therefore, we proposed the improvement based on the combination of total ratio cost matrix and total difference method by column without using classical ranking functions. …”
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Improved Segregated Advancement (I-SA): a new method for solving full triangular fuzzy transportation problems by Muhammad Sam’An, Muhammad Sam’An, Yosza Dasril, Yosza Dasril, Chandrasekar Ramasamy, Chandrasekar Ramasamy, Nazarudin Bujang, Nazarudin Bujang, Yahya Nur Ifriza, Yahya Nur Ifriza

“…Therefore, we proposed the improvement based on the combination of total ratio cost matrix and total difference method by column without using classical ranking functions. …”
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Improved Segregated Advancement (I-SA): a new method for solving full triangular fuzzy transportation problems by Muhammad Sam’An, Muhammad Sam’An, Yosza Dasril, Yosza Dasril, Chandrasekar Ramasamy, Chandrasekar Ramasamy, Nazarudin Bujang, Nazarudin Bujang, Yahya Nur Ifriza, Yahya Nur Ifriza

“…Therefore, we proposed the improvement based on the combination of total ratio cost matrix and total difference method by column without using classical ranking functions. …”
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Improved Segregated Advancement (I-SA): a new method for solving full triangular fuzzy transportation problems by Muhammad Sam’An, Muhammad Sam’An, Yosza Dasri, Yosza Dasri, Chandrasekar Ramasamy, Chandrasekar Ramasamy, Nazarudin Bujang, Nazarudin Bujang, Yahya Nur Ifriza, Yahya Nur Ifriza

“…Therefore, we proposed the improvement based on the combination of total ratio cost matrix and total difference method by column without using classical ranking functions. …”
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Improved Segregated Advancement (I-SA): a new method for solving full triangular fuzzy transportation problems by Muhammad Sam’An, Muhammad Sam’An, Yosza Dasril, Yosza Dasril, Chandrasekar Ramasamy, Chandrasekar Ramasamy, Nazarudin Bujang, Nazarudin Bujang, Yahya Nur Ifriza, Yahya Nur Ifriza

“…Therefore, we proposed the improvement based on the combination of total ratio cost matrix and total difference method by column without using classical ranking functions. …”
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