Search Results - (( intelligence ((based max) OR (based m)) algorithm ) OR ( intelligence system graph algorithm ))
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Hybrid bat algorithm for minimum dominating set problem
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Graph theory-based radial load flow analysis to solve the dynamic network reconfiguration problem
Published 2016“…This paper has presented an intelligent graph theory-based RLF analysis to solve "dynamic" problems. …”
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Utilization of Tabu search heuristic rules in sampling-based motion planning
Published 2023“…We also compare the performance of the algorithm with some of the well-known path planning approaches, including Bug1, Bug2, PRM, RRT and the Visibility Graph. …”
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Interference and Priority Aware Coexistence (IPC) Algorithm for Link Scheduling in IEEE 802.15.6 Based WBANs
Published 2019“…This information is later used to generate an interference graph of the sensors associated with the coordinator and perform link scheduling. …”
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A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots
Published 2022“…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
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Adaptive and optimized radio resource allocation algorithms for OFDMA based networks
Published 2015“…This thesis proposes a threshold based resource allocation that helps to schedule and grant resources intelligently to solve the problem alluded to above resulting in better overall system performance, enhancing the network experience for the users. …”
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Thesis -
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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…Firstly is by enhancing the learning algorithm of a neural-fuzzy network; and secondly by devising an ensemble model to combine the predictions from multiple neural-fuzzy networks using an agent-based framework. …”
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Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…It reduces the number of handovers by 29.7% and 26.9%, respectively, compared to the conventional RSSI based handover algorithm and the previous worked, mobility improved handover (MIHO) algorithm. …”
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Thesis -
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Modified HOS based Eigenvector algorithm for improvement of poor SNR of Seismic data
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WiMAX Traffic Forecasting Based On Artificial Intelligence Techniques
Published 2024thesis::doctoral thesis -
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…The first modeling technique applies graph algorithms to compute a new set of optimal weighted structural properties of C60 and C70 fullerenes. …”
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Thesis -
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Heuristic factors in ant system algorithm for course timetabling problem
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Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin
Published 2014“…One example of such a network is called WiMAX which is driven by WiMAX Forum based on IEEE 802.16 Wireless MAN standard. …”
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The application of neural networks and min-max algorithm in digital congkak
Published 2013“…To make it intelligent, its player agent was developed using a combination of Neural Networks and Min-Max algorithm. …”
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Optimization of Maximum Power Point Tracking (MPPT) of Photovoltaic System using Artificial Intelligence (AI) Algorithms
Published 2013“…Studies on the conventional and intelligent algorithms are conducted and a comparison between their efficiencies and drawbacks is presented. …”
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Final Year Project -
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Designing and Developing an Intelligent Congkak
Published 2011“…and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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