Search Results - intelligence _ ((tree algorithm) OR (((graph algorithm) OR (search algorithm))))

VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

“…Visualization techniques help in understanding the searching behaviour of Genetic Algorithm. lt also makes possible the user interactions during the searching process. …”
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Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm by Abed, S.A., Rais, H.M.

“…This paper investigates the swarm intelligence behaviour represented by a population-based approach called the bat algorithm (BA) to find the smallest set of nodes that dominate the graph. …”
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Hybrid bat algorithm for minimum dominating set problem by Abed, S.A., Rais, H.M.

“…In this paper, the stochastic search represented by hybrid swarm intelligence algorithm to find the smallest set of nodes that dominate the graph. …”
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African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

“…This paper proposes a new meta-heuristic approach to solving numerical and graph-based problems. The African buffalo algorithm evolved from an understanding of the animal's survival instincts and the search techniques they utilize in the African forests and savannahs; the search for the optimal path to pasture is aligned to their cooperative, intelligent, and social nature. …”
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A hybrid local search algorithm for minimum dominating set problems by Abed, S.A., Rais, H.M., Watada, J., Sabar, N.R.

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A hybrid local search algorithm for minimum dominating set problems by Abed, S.A., Rais, H.M., Watada, J., Sabar, N.R.

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Optimizing Tree-Based Contrast Subspace Mining Using Genetic Algorithm by Sia, Florence Fui Sze, Rayner Alfred

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Modeling of static and dynamic components of bio-nanorobotic systems by Gavgani, Hamidreza Khataee

“…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
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Solving a backtracking intelligently : a case study / Muthukkaruppan Annamalai by Annamalai, Muthukkaruppan

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Incorporating semantic similarity measure in genetic algorithm: an approach for searching the gene ontology terms by M. Othman, Razib, Deris, Safaai, M. Ilias, Rosli, Alashwal, Hany Taher Ahmed, Hassan, Rohayanti, Mohamed, Farhan

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Computational comparison of major proposed methods for graph partitioning problem by Rais, H.M., Abed, S.A., Watada, J.

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Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

“…Decision trees; Forecasting; Multilayer neural networks; Ozone; Predictive analytics; Support vector machines; Artificial intelligence techniques; Machine learning techniques; Multi layer perceptron; Optimization approach; Ozone concentration forecasting; Prediction accuracy; Stand-alone algorithm; Tropospheric ozone concentration; Learning systems; ozone; air quality; algorithm; concentration (composition); machine learning; optimization; ozone; prediction; theoretical study; air pollutant; air quality; artificial intelligence; artificial neural network; concentration (parameter); decision tree; feed forward neural network; forecasting; fuzzy system; human; measurement accuracy; multilayer perceptron; prediction; random forest; recurrent neural network; Review; support vector machine; systematic review…”

Neutralisation state driven single-agent search strategy for solving constraint satisfaction problem / Saajid Akram Ahmed Abuluaih by Ahmed Abuluaih, Saajid Akram

“…Since Constraint Satisfaction Problem (CSP) is an NP-complete problem, brute-force search algorithms such as Backtracking algorithm (BT) are required as the guarantee to find a solution, when there is one. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…Grid search cross validation (CV) is applied for hyperparameter tuning of the algorithms. …”
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Utilization of Tabu search heuristic rules in sampling-based motion planning by Khaksar W., Hong T.S., Sahari K.S.M., Khaksar M.

“…We propose a sampling-based algorithm for path planning in unknown environments using Tabu search. …”

A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots by Wan Daud, Wan Mohd Bukhari, Abu, Nur Syuhadah, Omar, Siti Nashayu, Sohaimeh, Shahirul Ashraf, Adli,, M. H.

“…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
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A Robust Graph Theoretic Solution of Routing in Intelligent Networks by Qureshi, M.A., Hassan, M.F., Ehsan, M.K., Khan, M.O., Ali, M.Y., Khan, S.

“…The fast construction of shortest-path tree (SPT) is important to devise an efficient routing in a nondelay tolerant networks. …”
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Intelligent technique for grading tropical fruit using magnetic resonance imaging by A. Balogun, Wasiu, Salami, Momoh Jimoh Emiyoka, J. McCarthy, Michael, Mohd Mustafah, Yasir, Aibinu, Abiodun Musa

“…Levenberg-Marquardt algorithm (trainlm) gave the best performance fitness out of different types of backpropagation algorithm used with least Mean Square Error (MSE) of 0.0814 corresponding to R-value of 0.8094. …”
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DisClose: Discovering colossal closed itemsets via a memory efficient compact row-tree by Zulkurnain , N.F., Haglin, David J., Keane, John A

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Knowledge-based system developement for the game congkak / Syah Ali Reza Yaacob by Yaacob, Syah Ali Reza

“…The agent will use Minimax and α-β pruning as the search algorithms. Game rules will act as the evaluation function, evaluating all moves created by the algorithms. …”
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