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A hybrid particle swarm optimization approach and its application to solving portfolio selection problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

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Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad by Mostafa, Modiri Delshad

“…Several case studies varied in size and complexity are employed in the power dispatch problems. Backtracking search algorithm (BSA) as the new evolutionary technique of optimization is used for solving the problems. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…Researchers have in the past few decades resorted to several methods that are inspired from complex optimization problems. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

“…Besides, since PSO operates in the continuous domain, it cannot be applied directly to solve a discrete problem like the JSP efficiently. This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

“…The basic bacteria foraging has been successful in solving single objective non-matrix space NP-hard optimization problems. …”
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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.

Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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Improving neural networks training using experiment design approach by Chong, Wei Kean

“…Randomly select the m data set for conventional training algorithm. …”
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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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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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Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

“…This algorithm is used to determine the vector i a that enables us to find the optimal parameters of ƒ(x)which is simplified as F(x)= ∑aᵢK(x,xᵢ) . …”
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian by Tey, Siew Kian

“…The application of orthogonal decomposition method using Householder transformation (refer to section 3.3) is used to solve the least-squares problem in power system state estimation. …”
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Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

“…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

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Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators by Abed I.A., Sahari K.S.M., Koh S.P., Tiong S.K., Jagadeesh P.

“…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”

Improved Multi-Verse Optimizer In Text Document Clustering For Topic Extraction by Abasi, Ammar Kamal Mousa

“…Second, three multi-verse optimizer algorithm (MVOs), namely, basic MVO, modified MVO, hybrid MVO is proposed to solve the TDC problem; these algorithms are incremental improvements of the preceding versions. …”
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Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah by Hanafiah, Sukri

“…After discussing about the introduction (the basic of CMOS transistor ), we will discuss how to create the Optimal layout of CMOS Functional Array with the minimum separation based on euler path method. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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