Search Results - (( intelligence based drops algorithm ) OR ( intelligence its graph algorithm ))

A lightweight graph-based pattern recognition scheme in mobile ad hoc networks. by Raja Mahmood, Raja Azlina, Muhamad Amin, Anang Hudaya, Amir, Amiza, Khan, Asad I.

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Intelligent Examination Timetabling System Using Hybrid Intelligent Water Drops Algorithm by AlDeeb, BA, Norwawi, NM, Al-Betar, MA, Jali, MZ

“…Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops. …”

Intelligent examination timetabling system using hybrid intelligent water drops algorithm by AlDeeb, Bashar A., Md Norwawi, Norita, Al-Betar, Mohammed A., Jali, Mohd Z.

“…This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM).Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops.The results of this study prove that the proposed algorithm can produce a high quality examination timetable in shorter time in comparison with the manual timetable.…”
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Solving university examination timetabling problem using intelligent water drops algorithm by Aldeeb B.A., Norwawi N.M., Al-Betar M.A., Jali M.Z.B.

Subjects: “…Intelligent water drops algorithm…”

Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications by O. F. Alijla, Basem

“…Pertama, algoritma TAC yang diubahsuai, diperkenalkan. The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
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Solving University Examination Timetabling Problem Using Intelligent Water Drops Algorithm by Aldeeb, BA, Norwawi, NM, Al-Betar, MA, Bin Jali, MZ

“…IWD is a recent metaheuristic population-based algorithm belonging to swarm intelligent category which simulate river system. …”

Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

“…This thesis presents an investigation of using the Intelligent Water Drops (IWD) algorithm to construct and produce good quality solutions for the UETP. …”

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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Optimization of Maximum Power Point Tracking (MPPT) of Photovoltaic System using Artificial Intelligence (AI) Algorithms by Raal Mandour, Raal

“…Studies on the conventional and intelligent algorithms are conducted and a comparison between their efficiencies and drawbacks is presented. …”
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Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm by Pham Q.B., Afan H.A., Mohammadi B., Ahmed A.N., Linh N.T.T., Vo N.D., Moazenzadeh R., Yu P.-S., El-Shafie A.

Attack prediction to enhance attack path discovery using improved attack graph by Al-Araji, Zaid Jasim, Abdullah, Raihana Syahirah, Syed Ahmad, Sharifah Sakinah

“…One such approach is attack graphs. The primary purpose of an attack graph is to not only predict an attack but its next steps within a network as well. …”
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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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Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph by Siti Mariatul Hazwa, Mohd Huzir, Anis Hazirah ‘Izzati H., Al-Hadi, Amir Hussairi, Zaidi, Nurlaila F., Ismail, Zakiah, Mohd Yusoff, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

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Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment by Perumal, Thinagaran

“…The third algorithm, named as Pro-Active Intelligence algorithm has inspired autonomous action triggering for each event interoperation, using a control action statement that is generated by SOAP packets required for joint execution of tasks among heterogeneous subsystems. …”
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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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Comparison performances between MABSA-PI controller and MABSA-PD controller for DC motor position system by Mohamad Harith Hilmi, Fajaffri, Nafrizuan, Mat Yahya

“…The MATLAB controllers are developed using the Simulink toolbox, while the transfer function of a DC motor is obtained from its circuit. Modified adaptive bats sonar algorithm (MABSA) will be implemented in the PI controller and PD controller as the main algorithm. …”
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Design and Development of Artificial Intelligence (Al)-Based Desicion Support System For Manufacturing Applications by Lim , Chee Peng

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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 also compare the performance of the algorithm with some of the well-known path planning approaches, including Bug1, Bug2, PRM, RRT and the Visibility Graph. …”