Search Results - (( mobile optimization means algorithm ) OR ( based observational bat algorithm ))

Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

“…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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Taguchi's T-method with nearest integer-based binary bat algorithm for prediction by Marlan Z.M., Jamaludin K.R., Ramlie F., Harudin N.

“…In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi�s T-method. …”

A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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Amtree Protocol Enhancement by Multicast Tree Modification and Incorporation of Multiple Sources by Al‐Sharafi, Ali Mohammed Ali

“…This means the time of optimization process is also high. …”
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A noble approach of ACO algorithm for WSN by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

“…A noble approach of ant colony optimization (ACO) algorithm for discovering the optimum route in the WSNs for data transmission is proposed here for enhancement and optimization considering the issue of path selection to reach the nodes. …”
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Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms by Annisa, Jamali, Intan Zaurah, Mat Darus, Hanim, Mohd Yatim, Mat Hussin, Ab Talib

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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…Secondly, the K-value-calculating algorithm computes the optimal number of clusters. …”

Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

“…It reduces the number of handovers by 29.7% and 26.9%, respectively, compared to the conventional RSSI based handover algorithm and the previous worked, mobility improved handover (MIHO) algorithm. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

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Mobility-aware Offloading Decision For Multi-access Edge Computing In 5g Networks by Saeid Jahandar, Lida Kouhalvandi, Ibraheem Shayea, Mustafa Ergen, Marwan Hadri Azmi, Hafizal Mohamad

A Fuzzy Hybrid GA-PSO Algorithm for Multi-Objective AGV Scheduling in FMS by Mousavi, M., Yap, Hwa Jen, Musa, S.N., Md Dawal, Siti Zawiah

“…A fuzzy hybrid GA-PSO (genetic algorithm – particle swarm optimization) algorithm was developed to optimize the model. …”
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Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization by Mousavi, M., Yap, Hwa Jen, Musa, S.N., Tahriri, F., Md Dawal, Siti Zawiah

“…In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. …”
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Acquisition of new subscribers using analytical models in the telecommunication industry / Nik Muhammad Naim Nik Ghazali by Nik Ghazali, Nik Muhammad Naim

“…The goal of using optimization is to minimize the number of acquisition while still meeting the set target mobile revenue. …”
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Design a new proposed route optimization scheme based NEMO-Centric MANEMO (NCM) by Mousa, Ahmed A., Hassan Abdalla Hashim, Aisha, Khateeb, Khalid Al, Khalifa, Othman Omran, Adibah, Huda Adibah

“…Route Optimization (RO) refers to any approach that optimizes the transmission of packets between a Mobile Network Node/Mobile Router and a Corresponding Node/Home Agent. …”
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CROWDSOURCING-BASED MOBILE APPLICATION FOR SUPERMARKET STOCK AVAILABILITY CHECKER by MOHD RUSLI, AMIRAH WAHIDAH

“…This project is implementing spatial crowdsourcing technology in hope to optimize the frequent updates of the stock availability by means of contributions from users. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

“…Extensive studies prove the proposed algorithm outperforms bat algorithm (BA), improved grey wolf optimizer (IGWO), conventional PSO and P&O, with convergence time shorter than 0.3 s and tracking accuracy above 99% under different complex PSCs. � 2010-2012 IEEE.…”

A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization by Ehteram M., Sammen S.S., Panahi F., Sidek L.M.

Exp-bet packet scheduling algorithm for multiple traffic services in long term evolution (LTE) system / Ku Siti Syahidah Ku Mohd Noh by Ku Mohd Noh, Ku Siti Syahidah

“…Most mobile devices today support multimedia services and legacy mobile services such as voice, short message service (SMS) and multimedia messaging service (MMS). …”
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Multi-criteria optimization framework for cloudlet computing in WMANs: integrating VL-WIDE and AHP for enhanced decision-making by Muwafaq, Layth, Noordin, Nor K, Othman, Mohamed, Ismail, Alyani, Hashim, Fazirulhisyam

“…Comprehensive time-series evaluations demonstrate that our framework significantly outperforms conventional systems and other benchmark algorithms, with VL-WIDE and AHP achieving the lowest root mean square error (RMSE) of 16.7, a 5.1% improvement over random selection. …”
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