Search Results - (( intelligence based ((data algorithm) OR (path algorithm)) ) OR ( intelligence _ bee algorithm ))

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  1. 1

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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    Monograph
  2. 2

    A quick gbest guided artificial bee colony algorithm for stock market prices prediction by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. …”
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    Article
  3. 3

    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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    Conference or Workshop Item
  4. 4

    Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

    Published 2018
    “…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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    Article
  5. 5

    Performance Analysis of Swarm Intelligence-Based Routing Protocol for Mobile Ad Hoc Network and Wireless Mesh Networks by Moghanjoughi, Ayyoub Akbari

    Published 2009
    “…Also the main aim of this research is to solve the freezing problem during optimum as well as sub-optimum path discovery process. In this research, Intelligent AntNet based Routing Algorithm (IANRA) is presented for routing in WMNs and MANET to find optimum and near-optimum paths for data packet routing. …”
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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
    “…It is proposed and shown that route-like intelligent motion is based on a combination of decisional and kinematical factors. …”
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    Thesis
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    Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph by Joseph, Corina

    Published 2023
    “…Corina delivering her speech titled "AI and SDGs: Resource-Based View Perspective." In the speech introduction, various definitions of Artificial Intelligence (AI) were provided. …”
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    Article
  13. 13

    Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization by Chiu, Po Chan, Ali, Selamat, Ondrej, Krejcar, Kuok, King Kuok

    Published 2021
    “…The fitness-dependent optimizer (FDO), a newly proposed swarm intelligent algorithm, is focused on the reproductive mechanism of bee swarming and collective decision-making. …”
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    Article
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    A Novel Map-matching Algorithm to Improve Vehicle Tracking System Accuracy by Dewandaru, Agung, Md Said, Abas, Matori, A. N.

    Published 2008
    “…The curve-to-curve matching algorithms measure the similarity between the track and possible road path. …”
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    Article
  16. 16

    Multi agent quality of service routing based on scheme ant colony optimization algorithm by Baygi, Maassoumeh Javadi

    Published 2014
    “…The proposed scheme has been simulated by OMNET++ and compared with standard AntNet and two well-known standard QoS routings; Widest Shortest Path (WSP) algorithm and Shortest Widest Path (SWP) algorithm. …”
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    Thesis
  17. 17

    A novel map-matching algorithm to improve vehicle tracking system accuracy by A.M., Said, A.N., Matori, A., Dewandaru

    Published 2007
    “…Point-to-curve matching algorithm is not suitable to the problem since it ignores any historical data and often gave unstable, jumping results. …”
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    Conference or Workshop Item
  18. 18

    Machine Learning and Dyslexia-Diagnostic and Classification System (DCS) for Kids with Learning Disabilities by Rehman Ullah, Khan, Julia Ai Cheng, Lee, Oon, Yin Bee

    Published 2018
    “…Most experts are using manual techniques to diagnose dyslexia. Machine learning algorithms are capable enough to learn the knowledge of experts and intelligently diagnose and classify dyslexics. …”
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    Article
  19. 19

    Efficient and scalable ant colony optimization based WSN routing protocol for IoT by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2020
    “…In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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    Article
  20. 20

    A Map-matching Algorithm to Improve Vehicle Tracking Systems Accuracy by Agung Dewandaru, Agung

    Published 2008
    “…The satellite-based vehicle tracking systems accuracy can be improved by augmenting the positional information using road network data, in a process known as map-niatcliing. …”
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    Final Year Project