Search Results - (( evolution optimization path algorithm ) OR ( problem representation learning 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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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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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

“…It is very important to handle this problem from the beginning before novices learn more advanced OOP concepts like encapsulation, inheritance, and polymorphism. …”
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Malicious URL Detection with Distributed Representation and Deep Learning by Do N.Q., Selamat A., Lim K.C., Krejcar O.

Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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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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Problem Solving by Yahaya, Azizi

“…Building on the previous work of yourself and others. Transfer of learning and viewing each problem as a learning opportunity. …”
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The influence of students’ concept of mole, problem representation ability and mathematical ability on stoichiometry problem solving by Taha, Hafsah, Hashim, Rosnani, Ismail, Zurida, Jusoff, Kamaruzaman, Khoo, Yin Yin

“…Students ought to be exposed and guided to understand the underlying conceptual foundation of stoichiometry before introducing the algorithmic way of solving the problems. Keywords: stoichiometry problem solving; mole concept; problem representation ability; mathematical ability…”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…Traditional schema theory does not support Lamatckian learning, i.e, forcing the genetic representation to match the solution found by the learning algorithm. …”
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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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Learning representations of network traffic using deep neural networks for network anomaly detection: A perspective towards oil and gas it infrastructures by Naseer, S., Ali, R.F., Dominic, P.D.D., Saleem, Y.

“…A total of sixty anomaly detectors were trained by authors using twelve conventional Machine Learning algorithms to compare the performance of aforementioned deep representations with that of a human-engineered handcrafted network data representation. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network by Kho, Liew Ching

“…The representation of 2 Satisfiability problem or 2SAT is increasingly viewed as a significant logical rule in order to synthesize many real life applications. …”
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Implementation of hashed cryptography algorithm based on cryptography message syntax by Ali, Mohammed Ahnaf

“…Hence, the fragmented CMS encryption algorithm will solve this problem and the errors in the message will be removed. …”
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Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification by Wong S.Y., Yap K.S., Zhai Q., Li X.