Search Results - (( intelligence a path algorithm ) OR ( intelligence based max algorithm ))*

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    Performance Analysis of Routing Protocols in Resource-Constrained Opportunistic Networks by Aref Hassan, Kurd Ali, Halikul, Lenando, Mohamad, Alrfaay, Slim, Chaoui, Haithem Ben, Chikha, Akram, Ajouli

    Published 2019
    “…To this end, we present in this paper a study on the performance analysis of six of the most popular routing protocols in opportunistic networks, namely, epidemic, PRoPHET, MaxProp, Spray and Wait, Spray and Focus, and Encounter-Based Routing (EBR). …”
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    New algorithm for autonomous dynamic path planning in real-time intelligent robot car by Mohammed, Akeel Ahmed, Hassan, Mohd Khair, Aris, Ishak, Kamsani, Noor Ain

    Published 2017
    “…Through the use of modified A* algorithm, the optimal path with a minimum cost can be determined and an efficient execution time of moving from a starting location to a target location in a dynamic environment can be achieved. …”
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  4. 4

    Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques by Salem S. M. Khalifa

    Published 2024
    “…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”
    thesis::doctoral thesis
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    Mobile robot path planning using hybrid genetic algorithm and traversability vectors method by Loo, C.K., Rajeswari, M., Wong, E.K., RaoTask, M.V.C.

    Published 2004
    “…However, the genetic algorithm path planning approach in the previous works requires a preprocessing step that captures the connectivity of the free-space in a concise representation. …”
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    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin by Alsahag, Ali Mohammed, Mohd Ali, Borhanuddin, Noordin, Nor Kamariah, Mohamad, Hafizal

    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 by Che Pa, Noraziah, Alwi, Asmidah, Mohamed Din, Aniza, Safwan, Muhammad

    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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    Conference or Workshop Item
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    A review : On intelligent mobile robot path planning techniques by Muhammad, Aisha, Ali, Mohammad A.H., Shanono, Ibrahim Haruna

    Published 2021
    “…This paper presents a brief review of the intelligent robot navigation methods. …”
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    Designing and Developing an Intelligent Congkak by Muhammad Safwan, Mohd Shahidan

    Published 2011
    “…and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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    Thesis
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    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    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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    Implementation of swarm intelligence algorithms on mobile robots by Kong, Zhung Jie

    Published 2017
    “…This thesis focusses on the implementation of swarm intelligence algorithms on multiple mobile robots. A scenario which could be used to display the swarm intelligence behavior is being designed in this thesis. …”
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    Undergraduates Project Papers
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    Performance Analysis of Swarm Intelligence-Based Routing Protocol for Mobile Ad Hoc Network and Wireless Mesh Networks by Moghanjoughi, Ayyoub Akbari

    Published 2009
    “…Ants’ algorithm belongs to the Swarm Intelligence (SI), which is proposed to find the shortest path. …”
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    Thesis
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    A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

    Published 2009
    “…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

    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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    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    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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    Thesis
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    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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