Search Results - (( evolution optimization path algorithm ) OR ( using iteration sensor algorithm ))

The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

“…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking by Shen, Jiazheng, Hong, Tang Sai, Fan, Luxin, Zhao, Ruixin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

“…The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). …”
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Path optimization using genetic algorithm evolution by Low C.Y., Chong K.H., Salleh K., Johnny K.S.P.

Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

“…Roadways and telephone systems are the examples of them. Genetic Algorithms (GA), pioneered by John Holland, applies the principle of evolution found in nature to the problem of finding an optimal solution. …”
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Differential evolution optimization for constrained routing in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Ahmed, Gharib Subhi Mahmoud, Anwar, Farhat, Zakaria, Omar

“…This solution addresses efficient and optimal routing path construction for cost and quality metrics of the application. …”
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Investigation of relaxation factor in landweber iterative algorithm for electrical capacitance tomography by Tian, Wenbin, Ramli, Mimi Faisyalini, Yang, Wuqiang, Sun, Jiangtao

“…It is crucial to select a suitable relaxation factor in iterative image reconstruction algorithms (e.g. Landweber iterative algorithm) for electrical capacitance tomography (ECT) because it affects the convergence. …”
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Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors by Binajjaj, Saeed Ali Saeed

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Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

“…Various algorithms can be applied in the optimization of machining problems; however, Differential Evolution is the most appropriate for use in chatter suppression, being less time consuming, locally optimal, and more robust than both Genetic Algorithms, despite their wide applications, and Sequential Quadratic Programming, which is a famous conventional algorithm.…”
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Characterization of gas-solid two-phase flow by using electrical capacitance tomography by Hamzah, Ahmad Azahari

“…To achieve these aims, three objectives are set: (i) determination of the optimum conditions for an AC-ECT system to measure the capacitance of poly(methyl methacrylate) (PMMA) material; (ii) determination of the average solid velocity using a cross-correlation method; and (iii) image reconstruction based on eight ECT sensors using iterative and non�iterative algorithms. …”
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Image reconstruction using iterative transpose algorithm for optical tomography by Md. Yunos, Yusri, Abd. Rahim, Ruzairi, Green, R. G., Fazalul Rahiman, Mohd. Hafiz

“…This paper describes a transpose algorithm for use with an optical tomography system. …”
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

“…By integrating the ABC algorithm into the manipulator's control system, the goal is to enhance its ability to plan paths and optimize trajectories. …”
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SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

“…Wireless sensor networks operate through commonly self-organized sensor nodes to transfer data in a multi-hop approach to a central sink. …”
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Evoluation strategy for collaborative beamforming in wireless sensor networks by Wong, Chen How

“…An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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Evolution strategy for collaborative beamforming in wireless sensor networks by Wong, Chen How

“…An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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Review of wire-mesh tomography in different experiments by Rajan, Navintiran, Ruzairi, Abdul Rahim, Mohd Shukri, Manaf, Mohd Hafiz, Fazalul Rahiman, Anita, Ahmad, Yusri, Md Yunus, Sallehudin, Ibrahim, Mimi Faisyalini, Ramli, Yasmin, Abdul Wahab, Suzanna, Ridzuan Aw Abdullah

“…This sensor can be used to gain void fraction distribution in multiphase flow visualization. …”
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Improving robot Darwinian particle swarm optimization using quantum-behaved swarm theory for robot exploration and communication / Duaa Mehiar by Duaa , Mehiar

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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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On Clustering Algorithm Of Coverage Area Problems In Wireless Sensor Networks by Ismail Abdullah, Kalid Abdlkader Marsal

“…In the case study, many algorithms have been proposed in the literature, in order to find the maximum number of disjoint or non-disjoint sets of sensor cover sets, we can see where one set can be active at any one time. …”

Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

“…This mechanism is restricted to search the possible solutions in a critical path. Modification on the path by using neighborhood search significantly reduces the total length of the makespan. …”
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Deriving the absorption coefficients of lattice mismatched InGaAs using genetic algorithm by Lee H.J., Ali Gamel M.M., Ker P.J., Jamaludin M.Z., Wong Y.H., Yap K.S., Willmott J.R., Hobbs M.J., David J.P.R., Tan C.H.

“…By selecting the best gene for the next iteration, the utilization of Genetic Algorithm has significantly reduced the number of iterations from a maximum of 10 000 to 300. …”