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A study of packet scheduling algorithms in long term evolution-advanced
Published 2019“…The simulation results obtained demonstrate the efficacy of RM2 scheduling algorithm over other scheduling algorithms in maximizing the system capacity and is more robust on the effect of the cellular channel impairments.…”
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Improving real-time multimedia scheduling in practical mobile cellular channels
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling
Published 2018“…To deal with this complicated problem, Series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed in this paper. …”
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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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Solving Economic Dispatch Problems with Practical Constraints Utilizing Differential Search Algorithm
Published 2013“…This paper presents a recent swarm intelligence technique namely Differential Search (DS) algorithm in solving Economic Dispatch (ED) problems with considering the practical constraints in power system. …”
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Conference or Workshop Item -
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Distributed learning based energy-efficient operations in small cell networks
Published 2023“…Additionally, an intelligent distributed cooperative power allocation learning algorithm is proposed to enhance energy efficiency in small cell networks while satisfying the scalability, power constraint, user association requirements, and QoS constraints. …”
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Power system stabilization based on artificial intelligent techniques: a review
Published 2009“…These techniques are Artificial Neural Network (ANN), fuzzy logic, hybrid artificial intelligent, expert systems, and optimization techniques base AI such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search (TS) algorithm, etc. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…Swarm intelligence algorithms are metaheuristic algorithms inspired by the simple interactions of biological organisms in a population. …”
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Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification
Published 2021“…Swarm intelligence-based feature selection techniques are implemented by this work to increase classifier performance in classifying Amphetamine-type Stimulants (ATS) drugs. …”
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Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications
Published 2024“…In academia, this study proposed an innovative SLR-MLR predictive algorithm and utilized a novel statistical approach to evaluate and select the superior predictive algorithm. …”
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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. …”
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Coordination of PSS and PID controller for power system stability enhancement - overview
Published 2023“…Swarm intelligence based coordinated controller (PID+PSS), will effectively enhance the small signal stability and transient stability in power system. …”
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Intelligent technique for grading tropical fruit using magnetic resonance imaging
Published 2013“…Recent application of modern marketing techniques coupled with intelligent agricultural systems of production has transformed small scale farming into large scale, in most part of the world. …”
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Malaysia solar energy experience: intelligent fault location algorithm for unbalanced radial distribution network including PV systems
Published 2016“…The results reveal that the presented algorithm using a small scale input set is able to precisely locate different fault types in the unbalanced distribution networks including DG units.…”
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