Search Results - (( java implication based algorithm ) OR ( based reactive learning algorithm ))

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    Unified strategy for intensification and diversification balance in ACO metaheuristic by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2017
    “…This intensification and diversification in Ant Colony Optimization (ACO) is the search strategy to achieve a trade-off between learning a new search experience (exploration) and earning from the previous experience (exploitation).The automation between the two processes is maintained using reactive search. …”
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    Conference or Workshop Item
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    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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    Thesis
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    Cross-reactive neutralizing antibody epitopes against Enterovirus 71 identified by an in silico approach by Kirk, Kristin, Poh, Chit Laa *, Fecondo, John, Pourianfar, Hamid Reza, Shaw, J., Grollo, Lara

    Published 2012
    “…A combined in silico approach utilizing computational hidden Markov model (HMM), propensity scale algorithm, and artificial learning, identified three 15-mer structurally conserved B-cell epitope candidates lying within the EV71 capsid proteins. …”
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    Article
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    A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

    Published 2009
    “…An ActivMedia Pioneer robot navigating under fuzzy artificial potential fields (APF) and blind-folded human subjects are the two types of intelligent travelers. The reactive motion of robots and path planning strategies of the blinds are similar in that both of them locally acquire knowledge and explore the space based on route-like spatial cognition. …”
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    Multi-hop and mesh for LoRa networks: Recent advancements, issues, and recommended applications by Andrew Wei-loong Wong, Say leng goh, Mohammad Kamrul Hasan, Salmah Fattah

    Published 2024
    “…The upcoming trend of implementing machine learning algorithms to multi-hop and mesh LoRa networks opens up a wide range of possibilities, ranging from airspace efficiency, efficient route selection, and improving data throughput. …”
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    Article
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    Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

    Published 2017
    “…Firstly, a new sensor-based online approach is planned to reach the first and second objective of the research. …”
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    Thesis
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    A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields by Motlagh, Omid Reza Esmaeili, Tang, Sai Hong, Ramli, Abdul Rahman, Ismail, Napsiah, Nakhaeinia, Danial

    Published 2010
    “…A novel decision modeling technique is developed based on capabilities of the fuzzy cognitive map (FCM) and supervised learning using the genetic algorithm (GA). …”
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    Conference or Workshop Item
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    Prototype development of Web AI-based decision support system: insights and recommendations for satellite anomaly identification by Mutholib, Abdul, Abdul Rahim, Nadirah, Gunawan, Teddy Surya

    Published 2025
    “…The proposed Web AI-based DSS framework integrates Machine Learning (ML) based Trade-Space Exploration (TSE) as the model base and Generative AI as the knowledge base to offer insights and recommendations for anomaly prevention and decision making prior to the launch of the satellite into orbit. …”
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    Proceeding Paper
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    Near-infrared spectroscopy modeling of combustion characteristics in chip and ground biomass from fast-growing trees and agricultural residue by Shrestha, Bijendra, Posom, Jetsada, Pornchaloempong, Pimpen, Sirisomboon, Panmanas, Shrestha, Bim Prasad, Ariffin, Hidayah

    Published 2024
    “…However, including more representative samples and exploring a more suitable machine learning algorithm are essential for updating the model to achieve a better nondestructive assessment of biomass combustion behavior.…”
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    Article