Search Results - (( java implication based algorithm ) OR ( based association problem algorithm ))
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Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi
Published 2025“…The proposed optimization problem is divided into three subproblems. First, a greedy-based user association algorithm is proposed to allocate multiple users to MBS or SBSs to maximize the total sum rate. …”
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Solving 0/1 Knapsack Problem using Opposition-based Whale Optimization Algorithm (OWOA)
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On Newton-Raphson formulation and algorithm for displacement based structural dynamics problem with quadratic damping nonlinearity
Published 2017“…Quadratic damping nonlinearity is challenging for displacement based structural dynamics problem as the problem is nonlinear in time derivative of the primitive variable. …”
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems
Published 2018“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023“…This work is focused on the implementation of evolutionary based computer algorithms, genetic algorithms (GAs), on microcontrollers. …”
Conference paper -
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Solving multi-task optimization problems using the sine cosine algorithm
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
Published 2019“…The proposed and the benchmark algorithms are tested for large-scale optimization problems which are associated with high-dimensional variability. …”
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A Rough-Apriori Technique in Mining Linguistic Association Rules
Published 2008“…This paper has proposed a rough-Apriori based mining technique in mining linguistic association rules focusing on the problem of capturing the numerical interval with linguistic terms in quantitative association rules mining. …”
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Book Chapter -
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Renovation explicit dynamic procedures by application of Trujillo algorithm
Published 2011“…In this paper, a Trujillo algorithm method for the exact solution of nonlinear explicit dynamic problems is developed. …”
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Distributed learning based energy-efficient operations in small cell networks
Published 2023“…Several solutions proposed in the literature are limited to addressing the cooperation problem and resource management issues. The joint optimisation problem of user association and power allocation has been studied extensively; however, conventional optimisation techniques still have room for improvement in distributed resource management strategies that evolve based on network dynamics. …”
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An efficient likelihood-based modulation classification algorithm for multiple-input multiple-output systems
Published 2016“…To overcome the problems associated with the existing likelihood-based MC algorithms, a new algorithm is developed in this paper. …”
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Cuckoo Search Approach for Cutting Stock Problem
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…Evolutionary algorithms have been extensively used to resolve problems associated with multiple and often conflicting objectives. …”
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A smart guidance indoor parking system based on Dijkstra's algorithm and ant colony algorithm
Published 2020“…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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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Modified ACS centroid memory for data clustering
Published 2019“…Ant Colony Optimization for Clustering (ACOC) is a swarm algorithm inspired from nature to solve clustering issues as optimization problems. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification
Published 2014“…On the other hand maximal itemset based association rules, that are a subset of closed itemset based rules, show to be insufficient in this regard, and typically will have worse recall and generalization power. …”
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