Search Results - (( intelligence practices scheduling algorithm ) OR ( intelligence based learning algorithm ))
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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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Developing an intelligent system to acquire meeting knowledge in problem-based learning environments
Published 2006“…MALESAbrain1-3 is an intelligent algorithm which originally is designed for problem-based learning (PBL) environment. …”
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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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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
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Development of an intelligent prediction tool for rice yield based on machine learning techniques
Published 2006“…Intelligent systems based on machine learning techniques. such as classification. clustering. are gaining Wide spread popularity in real world applications. …”
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Design of Modeling Elements of Luoshan Shadow Puppets Creative Goods Based on Deep Learning
Published 2023“…Based on the design of modeling elements of Luoshan shadow puppets, this paper analyzes the characteristics of visual elements of shadow puppet creative goods, puts forward an intelligent design algorithm of shadow puppet creative goods based on DL, and explores the computer-aided shadow puppets modeling design strategy driven by artificial intelligence. …”
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Proceeding -
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A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network
Published 2024“…This study proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. …”
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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed
Published 2024Subjects:Conference Paper -
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…The application of artificial intelligence techniques (e.g., machine learning and deep learning) in medical science is becoming increasingly important for intelligently transforming all available information into valuable knowledge. …”
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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…In order to develop an intelligent agent, various programming techniques are used in achieving the property of self learning, information retrieval and searching algorithm. …”
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Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband
Published 2014“…Later, we investigate the game based-FQL algorithm by combining the game theoretic approach and the fuzzy Q-learning algorithm. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence
Published 2025“…This study intends to develop a Spatial Temporal-Graph Convolutional Network (ST-GCN) action detection algorithm based on the MediaPipe framework. This is achieved by integrating deep learning and artificial intelligence technologies. …”
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E4ML: Educational Tool for Machine Learning
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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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