Search Results - (( mobile location based algorithm ) OR ( _ application ant algorithm ))
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…This work examines the location determination techniques by attempting to determine the location of mobile users by taking advantage of SS and SQ history data and modeling the locations using the ELM algorithm. …”
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…This work examines the location determination techniques by attempting to determine the location of mobile users by taking advantage of SS and SQ history data and modeling the locations using the ELM algorithm. …”
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Mobile user location prediction: genetic algorithm-based approach
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Ant colony optimization in dynamic environments
Published 2010“…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
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The child tracker using location awareness / Muhammad Idham Amdan
Published 2017“…One the significance feature of this project is to track the position of device precisely. The location retrieve from client or the tracked device will be computed and filtered based on the algorithm to generate addresses from latitude and longitude, the coordinate of mobile phone. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Enhanced location and positioning in wimax networks with virtual mimo base station
Published 2015“…Furthermore, a new hybrid algorithm enhancement of mobile station (MS) location estimation by using a single MIMO base station (SMBS) with the virtual base station has been introduced. …”
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Interacted Multiple Ant Colonies for Search Stagnation Problem
Published 2010“…Ant Colony Optimization (ACO) is a successful application of swarm intelligence. …”
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Simulation of Virtual MIMO Base Stations for Mobile Location in IMT-Advanced Networks
Published 2012“…The conventional Location and Positioning (L&P) methods rely on availability of base station (BS) locations as well as mitigation of propagation effects. …”
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Autonomous path planning robot using geographical information
Published 2008“…The guidance algorithm is formed based on an initial direction and distance of the target location without considering the time taken by the robot to reach the desired destination. …”
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Improved Location And Positioning Utilizing Single MIMO Base Station In IMT-Advanced System
Published 2016“…The Single MIMO Base Station (SMBS) in mobile WiMAX is combined with a virtual technique, known as the Virtual Base Stations, created a novel algorithm for location and positioning (L&P) purposes. …”
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A new multicast-based architecture to support host mobility in IPv6
Published 2003“…A new multicast group joidleave mechanism for mobile nodes (MNs) is proposed. The mechanism is based on hash algorithm. …”
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Proceeding Paper -
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An Enhanced Ant Colony Optimisation Algorithm with the Hellinger Distance for Shariah-Compliant Securities Companies Bankruptcy Prediction
Published 2024“…The application of ant colony optimization (ACO) algorithms has been limited by their performance on imbalanced datasets, particularly within bankruptcy prediction where the some of bankruptcy cases lead to skewed data distributions. …”
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A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism
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A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…First, the high dependability on multi-attributes (location and time) of packets in random mobile sensors. …”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid
Published 2012“…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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