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  1. 1
    Implementation of an intelligent SINS navigator based on ANFIS

    Implementation of an intelligent SINS navigator based on ANFIS by Ahjebory, Karim M., Ismaeel, Salam A., Alqaissi, Ahmed M.

    Published 2009
    “…As in previous work, which is based on Artificial Neural Network, the window based weight updating strategy was used, and the intelligent navigator evaluated using several SINS hypothetical field tests data. …”
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  2. 2
    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data

    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data by Shakir, Mohamed, Malik, Aamir Saeed, Kamel, Nidal S., Qidwai, Uvais

    Published 2014
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  3. 3
    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data

    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
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  4. 4
    Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification

    Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

    Published 2019
    “…The proposed technique was evaluated using the publicly available epileptic seizure data from the machine learning repository of the UCI center for machine learning and intelligent systems. …”
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  5. 5
    Network calculus-based latency for time-triggered traffic under Flexible Window-Overlapping Scheduling (FWOS) in a Time-Sensitive Network (TSN)

    Network calculus-based latency for time-triggered traffic under Flexible Window-Overlapping Scheduling (FWOS) in a Time-Sensitive Network (TSN) by Shalghum, Khaled M., Noordin, Nor Kamariah, Sali, Aduwati, Hashim, Fazirulhisyam

    Published 2021
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  6. 6
    Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning

    Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning by Yingbei, Niu, Chai, Soo See

    Published 2026
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  7. 7
    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption

    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

    Published 2019
    “…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. …”
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  8. 8
    Time series data intelligent clustering algorithm for landslide displacement prediction

    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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  9. 9
    A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption

    A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption by Haruna, Chiroma, Abdullahi, Usman Ali, Targio Hashem, Ibrahim Abaker, Saadi, Younes, Al-Dabbagh, Rawaa Dawoud, Ahmad, Muhammad Murtala, Emmanuel Dada, Gbenga, Danjuma, Sani, Maitama, Jaafar Zubairu, Abubakar, Adamu, Abdulhamid, Shafi’i Muhammad

    Published 2019
    “…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. …”
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  10. 10
    Investigating the Application of Artificial Intelligence for Earthquake Prediction in Terengganu

    Investigating the Application of Artificial Intelligence for Earthquake Prediction in Terengganu by Suzlyana Marhain binti Masrizan

    Published 2023
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  11. 11
    A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm

    A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm by Adam, A.A., Soleimani, H., Shukur, M.F.B.A., Dennis, J.O., Abdulkadir, B.A., Hassan, Y.M., Yusuf, J.Y., Shamsuri, N.A.B.

    Published 2022
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  12. 12
    A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm

    A new approach to understanding the interaction effect of salt and plasticizer on solid polymer electrolytes using statistical model and artificial intelligence algorithm by Adam, A.A., Soleimani, H., Shukur, M.F.B.A., Dennis, J.O., Abdulkadir, B.A., Hassan, Y.M., Yusuf, J.Y., Shamsuri, N.A.B.

    Published 2022
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  13. 13
    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun

    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

    Published 2000
    “…Indexer" to decide and index the relevant web pages, and ''Search algorithm" to retrieve the data from the results of indexing. …”
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  14. 14
    Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach

    Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach by Dalbouh H.A., Md Norwawi N.

    Published 2024
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  15. 15
    Snake detection system using convolutional neural network / Muhammad Danial Ahmad Tarmizi

    Snake detection system using convolutional neural network / Muhammad Danial Ahmad Tarmizi by Ahmad Tarmizi, Muhammad Danial

    Published 2020
    “…The algorithm is built using Tensorflow software. The development of the project is based on Waterfall methodology. …”
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  16. 16
    An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms

    An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms by Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain

    Published 2022
    “…This fusion of data science, artificial intelligence, and electrical energy management has turned out to be the most precise and robust energy management solution. …”
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  17. 17
    A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification

    A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification by Sa'ad, Mohamad Iqbal

    Published 2006
    “…These studies will help in choosing the right training algorithm for classification problem involved. These intelligent systems have to classify flow regimes in a closed line with the data are provided by Electrical Capacitance Tomography (ECT). …”
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    Monograph
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  18. 18
    The disruptometer: an artificial intelligence algorithm for market insights

    The disruptometer: an artificial intelligence algorithm for market insights by Wan Nordin, Mimi Aminah, Vedenyapin, Dmitry, Alghifari, Muhammad Fahreza, Gunawan, Teddy Surya

    Published 2019
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  19. 19
    Two objectives big data task scheduling using swarm intelligence in cloud computing

    Two objectives big data task scheduling using swarm intelligence in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke, Islam, Shayla, Zarir, Abdullah Ahmad

    Published 2016
    “…However, these scheduling algorithms vary in term of their performance and most of these traditional and simple scheduling algorithms may not be efficient for large scale data. …”
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  20. 20
    Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets

    Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets by Adedayo, Ojo O., Mohd Isa, Maryam, Che Soh, Azura, Abbas, Zulkifly

    Published 2014
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