Search Results - (( initial solution clustering algorithm ) OR ( evolution optimization path 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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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
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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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Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation by Tan , Khang Siang

“…However, it is very sensitive to the initialization conditions of number of clusters and initial cluster centres. …”
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Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

“…This makes the algorithm deviate from the clustering solution and performs a biased exploration. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Arabic Text Clustering Methods And Suggested Solutions For Theme-based Quran Clustering: Analysis Of Literature by Qusay Bsoul, Jaffar Atwan, Rosalina Abdul Salam, Malik Jawarneh

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…For the third problem a modified of Kohonen Network (MKN) algorithm was proposed to select the initial centres of clusters. …”
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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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Solving traveling salesman problem on cluster compute nodes by I.A., Aziz, Haron, N., Mehat, M., Jung, L.T., Mustapa, A.N., Akir, E.A.P.

“…The sequential algorithm is then converted into a parallel algorithm by integrating it with the Message Passing Interface (MPI) libraries so that it can be executed on a cluster computer. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…The preprocessing phase utilizes Canopy clustering to expedite the initial partitioning of data points, which are subsequently refined by K-means to enhance clustering performance. …”

Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition by Kasim, Nur Adilla, Nuawi, Mohd Zaki, Abdul Ghani, Jaharah, Ngatiman, Nor Azazi, Che Haron, Che Hassan, Muhammad Rizal

“…Nevertheless, the algorithm is sensitive to the initial centroids giving various solution every time the system updating. …”
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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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Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach by Othman, Khairulnizam

“…In addition, a new image clustering algorithm anticipates the need for largescale serial and parallel processing. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…Next the problem of data classification is studied as a problem of global, non-smooth and non-convex optimization; this approach consists of describing clusters for the given training sets. The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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