Search Results - (( using optimization method algorithm ) OR ( ii optimization sensor algorithm ))

Global optimization method for continuous - Time sensor scheduling by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan C.

“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applicatio... by Shehadeh, Hisham A., Idris, Mohd Yamani Idna, Ahmedy, Ismail, Ramli, Roziana, Noor, Noorzaily Mohamed

“…Our proposed method, named Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP), along with other three state-of-The-Art multi-objective optimization algorithms known as OMOPSO, NSGA-II and SPEA2, are utilized in this study. …”
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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

“…Methods: It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. …”
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A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles by Abdulhasan Al-Jarah, Ali Husam

“…Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. …”
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IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…The proposed algorithm, named Intelligent Water Drops with Simulated Annealing (IWDSA), combines two powerful optimization methods: Intelligent Water Drops (IWD) and Simulated Annealing (SA). …”
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Metaheuristic optimization techniques for localization in outdoor wireless sensor networks: a comprehensive review by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…This paper serves as a comprehensive background on localization algorithms and methods used in wireless sensor networks, offering insights for researchers to develop efficient localization algorithms tailored to specific application requirements in diverse work environments.…”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

“…The method adapts the original Non-Dominated Sorting Genetic Algorithm II (NSGA-II) by introducing a hybridisation of adaptive multi-parent crossover genetic algorithm and fuzzy dominance-based decomposition techniques. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

“…The method adapts the original Non-Dominated Sorting Genetic Algorithm II (NSGA-II) by introducing a hybridisation of adaptive multi-parent crossover genetic algorithm and fuzzy dominance-based decomposition techniques. …”
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Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Sebastian, P., Hamid, N.H.B., Ahmed, E.F.

“…This article explores the efficiency of the visual sensor placement based on a combination of two methods namely, a deterministic risk estimation for the risk assessment and a dynamic programming for optimizing the placement of surveillance cameras. …”
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Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

“…The AFW algorithm reduces unnecessary computations by focusing only on useful edge entries in the graph, thereby expediting the optimization process. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. SKF is compared with conventional algorithms for image template matching which are performance index value (PIM) and correlation by using DC components of image (TMC) and by using power of images (TMP) methods. …”
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Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

“…In order to solve the camera placement problem, a crucial fundamental step is modeling the coverage of the cameras in use. Following the coverage modeling, an optimization method needs to be used to locate the optimal poses and/or camera positions. …”
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A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

“…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

“…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
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A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

“…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
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Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization by Shaikh, Muhammad Suhail, Wang, Chang, Xie, Senlin, Zheng, Gengzhong, Dong, Xiaoqing, Qiu, Shuwei, Mohd Ashraf, Ahmad, Raj, Saurav

“…The Grey Wolf Optimizer (GWO) is enhanced using a chaotic map, improving its ability to find the best solutions and achieve faster convergence, resulting in the ICGWO algorithm. …”
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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks by Han, Fengrong, Izzeldin, Ibrahim Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue, Li, Ning

“…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…The experimental results demonstrate that the DSA optimized RFR algorithm achieves RMSE of 0.382% in the HPPC test using LiNMC battery. …”

Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa’

“…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection 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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