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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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Implementation of an intelligent SINS navigator based on ANFIS
Published 2009“…In this work an intelligent navigator developed to overcome the limitations of existing Strapdown Inertial Navigation Systems (SINS) algorithm. …”
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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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Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows
Published 2022“…The Artificial Bee Colony (ABC) is a popular swarm intelligence algorithm for COP. In this study, existing Modified ABC (MABC) algorithm is revised to solve the VRPTW. …”
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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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Snake detection system using convolutional neural network / Muhammad Danial Ahmad Tarmizi
Published 2020“…Objectives of this project is to design the flow of the system, developed in Window application and test the functionality of the system and reliability for the predictive model. …”
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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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A study of frame timing synchronization for WiMAX applications
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Genetic algorithm for event scheduling system
Published 2010“…UTeM’s Event Alert System (UTeM-EAS) is an improved version of previous Event Alert System in Universiti Teknikal Malaysia Melaka (UTeM) official site that aims to apply Artificial Intelligence (AI) in order to provide its users with events priority. …”
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Simulation and Visualization of TSP Using Ant Colony Optimization
Published 2023“…The Travelling Salesman Problem (TSP) is a well-known algorithmic problem its main objective is optimization. …”
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Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data
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Experiment and analysis of computer vision-based wrist radial and ulnar deviation exercises
Published 2017“…The hand tracking, center of palm detection and fingertips detection and Kinect sensor are used in this exercise system. This system guides the user to perform the radial and ulnar deviation movements through the user's display window. …”
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An Effective Power Dispatch Strategy for Clustered Micro-grids while Implementing Optimal Energy Management and Power Sharing Control using Power Line Communication
Published 2019“…Frequency shift keying (FSK) technique has been adopted for transmitting the binary signal over the power line communication (PLC). A part of the algorithm is utilized to deal with the optimal scheduling control while the other actuates the dynamic demand response based Photovoltaic (PV) power forecasting. …”
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