Search Results - (( developing integration bees algorithm ) OR ( java application stemming algorithm ))

Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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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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Autonomous reconnaissance mission: development of an algorithm for collaborative multi robot communication by Ahmed, Mohiuddin, Khan, Md. Raisuddin, Billah, Md. Masum

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

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Gps solution for active queue management using android platform by Liu, Yu Yao

“…Since queueing in different locations is considered as a optimisation problem, several algorithms are reviewed to tackle the problem, such as brute force method, nearest neighbour algorithm, and branch and bound algorithm. …”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Optimization of supply chain management by simulation based RFID with XBEE Network by Soomro, Aftab Ahmed

“…Thus, its communication range was enhanced by the integration of RFID with XBee (ZigBee) wireless mesh network devices. …”
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Localisation of inspection probes in a storage tank by Rosli, Nurmi Elisya, Sophian, Ali, Ashraf, Arselan

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Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

“…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

“…Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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Design And Implementation Of Human Crowd Density Estimation System With Energy Harvesting In Wireless Sensor Network Platform by Fadhlullah, Solahuddin Yusuf

“…These factors are then integrated into the proposed H-CDE algorithm. The H-CDE algorithm and its crowd classification yielded an average of 71.2 % accuracy in identifying the level of crowd density, which is the best compared to other algorithms found in the literature. …”
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