Search Results - (( developing integration colony algorithm ) OR ( java implication based algorithm ))

Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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PID-Controller Tuning of Brushless DC Motor by Using ACO (Ant Colony Optimization) Technique by SIAW KAH , JING

“…At the testing stage, the ACO algorithm is developed by using MATLAB. The ACO algorithm will calculate the ISE (Integral Square Error) for each set of PID parameters. and then comparison is done on the different values of ISE from different sets of PID parameters to choose the best PID parameters set with the lowest ISE. …”
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A smart guidance indoor parking system based on Dijkstra's algorithm and ant colony algorithm by Mohammad Ata, Karimeh Ibrahim, Che Soh, Azura, Ishak, Asnor Juraiza, Jaafar, Haslina

“…This paper introduces a smart guidance indoor parking system based on embedded system integrated with both the Dijkstra's algorithm and Ant Colony algorithm (ACO) to provide drivers with an efficient path to the nearest parking bay. …”
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A trust aware secure ant colony optimization based routing algorithm for Internet of Things by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A., Hassan Abdalla Hashim, Aisha

“…The adoption of bio-inspired approaches contributes to discovering the optimal path for IoT routing by modeling the cognitive behavior of insect colonies to attain security cost-effectively. For wireless sensor network (WSN) integrated dynamic IoT networks, this paper presents a trust-aware secure Ant colony optimization (ACO)-based routing algorithm to provide security while searching for an energy-efficient optimal routing path. …”
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Proportional integral derivative controller based on ant colony optimization for vibration cancellation of horizontal flexible plate structure by Muhammad Izzuddin Akmal, Zamri, Muhamad Sukri, Hadi, Aida Nur Syafiqah, Shaari, Nadzirah, Mohd Mokhtar

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Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices by Ali Abdallah, Ali Emhemed

“…The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
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Identifying a Gene Knockout Strategy Using a Hybrid of Simple Constrained Artificial Bee Colony Algorithm and Flux Balance Analysis to Enhance the Production of Succinate and Lacta... by Mei, Kie Hon, Mohd Saberi, Mohamad, Abdul Hakim, Mohamed Salleh, Yee, Wen Choon, Kauthar, Mohd Daud, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Omatu, Sigeru, Sinnott, Richard O., Corchado, Juan Manuel

“…The objective function of the hybrid algorithm is optimized using a swarm intelligence optimization algorithm and a Simple Constrained Artificial Bee Colony (SCABC) algorithm. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

“…These reviewed algorithms were mainly developed to solve continuous MOPs. …”
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Railway shortest path planner application using ant colony optimization algorithm / Muhammad Hassan Firdaus Ruslan by Ruslan, Muhammad Hassan Firdaus

“…For the process module, Ant Colony Optimization (ACO) algorithm was used to find the shortest path. …”
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DC Motor Control using Ant Colony Optimization by Amr Mansour, Sara

“…Since 1995 various other extended versions of AS have been developed, induding Ant Colony System (ACS) and MAX-MIN Ant System (MMAS). …”
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A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

“…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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Intelligent Tuning of PID Controller for Double-Link Flexible Robotic Arm Manipulator by Artificial Bee Colony Algorithm by Jamali, Annisa, Mat Darus, I.Z., Yatim, H.M, A. Talib, M. H., Hadi, M.S, Tokhi, M.O.

“…This research focuses on the development of intelligent controller utilizing artificial bee colony (ABC) algorithm to tune proportional integral derivative (PID) parameters for controlling two-link flexible manipulator (TLFRM). …”
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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Optimization in active vibration control: virtual experimentation using COMSOL multiphysics - MATLAB integration by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

“…Subsequently, it is exploring into the development of random approaches based on MABSA, integrating components into others algorithm whereby Squirrel Search Algorithm (SSA), Cauchy Mutation (CM) approach, and Doppler Effect (DE) phenomenon. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Optimization of transesterification process for Ceiba pentandra oil: A comparative study between kernel-based extreme learning machine and artificial neural networks by Kusumo F., Silitonga A.S., Masjuki H.H., Ong H.C., Siswantoro J., Mahlia T.M.I.

IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…Additionally, simulation results confirm that the proposed algorithm IWDSA exhibits outstanding performance compared to other algorithms utilizing optimization techniques, including genetic algorithms, bat algorithms, ant colony optimization, and swarm optimization. …”
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