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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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Modelling of multi-robot system for search and rescue by Poy, Yi Ler

“…In this project, this sensor-based algorithm is known as the Obstacle Avoidance Algorithm. …”
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Optimization Method Using Modified Harmony Search For Coverage And Energy Efficiency In Wireless Sensor Network by Halim, Nurul Hamimi

“…Coverage and energy efficiency metrics are two fundamental issues for almost all types of application in wireless sensor network (WSNs).Coverage reflects how well an area is monitored by sensor nodes and in energy efficient networks where less energy is consumed to provide the same level of services.These twin specifics are presented to evaluate the performance of a wireless sensor network.Due to its simplicity and ease of analysis,full coverage is widely implemented in many theoretical studies.However,sometimes full coverage is not the best way to represent some real-world application due to its strong restrictions and its deterministic characteristics.In this thesis,Modified Harmony Search algorithm (MHS) is proposed to achieve a sensor node deployment such that the covered area is optimal and data transfer has low energy consumption.Through computer simulations, experimental results verified that the proposed method improved the coverage of area in compare to some related methods.Based on the result obtain from every experiments,coverage area percentage performance is affected by the number of hotspots.This is shown by Harmony Search (HS) based method where the coverage area percentage increases as the number of hotspot increase. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

“…In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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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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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

“…In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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State of Charge Estimation for Lithium-Ion Battery Using Recurrent NARX Neural Network Model Based Lighting Search Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Blaabjerg F.

Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

“…Based on visual sensor parameters information, and the features of the area to be monitored, this paper uses a deterministic modeling approach to model the sensor coverage in a 2-D space. …”
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Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

“…Based on visual sensor parameters information, and the features of the area to be monitored, this paper uses a deterministic modeling approach to model the sensor coverage in a 2-D space. …”
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An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines by Bala, A., Ismail, I., Ibrahim, R., Sait, S.M., Oliva, D.

“…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

“…In this research, a Mobile Data Gathering based Network Layout (MDG-NL) algorithm is proposed. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

“…Due to the high complexity of these problems, metaheuristic based global optimization techniques are usually required. …”
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Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique by Mohd Mawardi, Saari, Mohd Herwan, Sulaiman, Kiwa, Toshihiko

“…In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

“…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. …”
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A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming by Darzi S., Sieh Kiong T., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

A Multi-State Gravitational Search Algorithm for Combinatorial Optimization Problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

“…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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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

“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

“…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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