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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
    An intelligent system based on kernel methods for crop yield prediction

    An intelligent system based on kernel methods for crop yield prediction by Majid Awan, A., Md. Sap, Mohd. Noor

    Published 2006
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  3. 3
    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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  4. 4
    Feature-based face recognition system using utilized artificial neural network

    Feature-based face recognition system using utilized artificial neural network by Chai, Tong Yuen

    Published 2010
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  5. 5
    An Intelligent Hybrid Model Using CNN and RNN for Crop Yield Prediction

    An Intelligent Hybrid Model Using CNN and RNN for Crop Yield Prediction by JUNE, KHOO YAN

    Published 2023
    “…AI has been successfully applied in agriculture field in terms of prediction, decision making, crops and soil monitoring and analysing. In this study, an intelligent hybrid model using CNN and RNN for crop yield prediction is proposed. …”
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    Final Year Project Report / IMRAD
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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
    Development Of An Intelligent Water Blending System For Irrigation Of Crops With Various Salinity Tolerance And Aquaculture

    Development Of An Intelligent Water Blending System For Irrigation Of Crops With Various Salinity Tolerance And Aquaculture by Abdullah Al-Jughaiman, Abdullah Sulaiman

    Published 2008
    “…The application of Artificial Intelligence (AI) systems in decision-making and intelligent control systems has recently gained attention of researchers. …”
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  8. 8
    How Can Aerial Imagery and Vegetation Indices Algorithms Monitor the Geotagged Crop?

    How Can Aerial Imagery and Vegetation Indices Algorithms Monitor the Geotagged Crop? by Vikneswaran Jeya Kumaran, Nur Adibah Mohidem, Nik Norasma Che’Ya, Wan Fazilah Fazlil Ilahi, Jasmin Arif Shah, Zulhilmy Sahwee, Norhakim Yusof, Mohammad Husni Omar

    Published 2024
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  9. 9
    How can aerial imagery and vegetation indices algorithms monitor the geotagged crop?

    How can aerial imagery and vegetation indices algorithms monitor the geotagged crop? by Jeya Kumaran, Vikneswaran, Mohidem, Nur Adibah, Che'Ya, Nik Norasma, Fazlil Ilahi, Wan Fazilah, Arif Shah, Jasmin, Sahwee, Zulhilmy, Yusof, Norhakim, Omar, Mohammad Husni

    Published 2024
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  10. 10
    Genetic Algorithm for Forecasting Bioinformatic Outcomes of Mutation-induced Cowpeas for Sustainable Development

    Genetic Algorithm for Forecasting Bioinformatic Outcomes of Mutation-induced Cowpeas for Sustainable Development by Kehinde, Okewu, Emmanuel, Okewu, Wong, Ling Shing, Siti Sarah, Maidin

    Published 2023
    “…To demonstrate the practicality of using artificial intelligence (AI) to address these problems, the genetic algorithm is applied to genetic engineering (genetic mutation) of cowpea in a crop improvement program to generate useful bioinformatic information for further improvement of the crop. …”
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  11. 11
    Smart agriculture: precision farming through sensor-based crop monitoring and control system

    Smart agriculture: precision farming through sensor-based crop monitoring and control system by Mohamad Hakhrani, Asyful Azhim, Abdul Hamid, Syamsul Bahrin

    Published 2024
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  12. 12
    Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT

    Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT by Rathinam R., Kasinathan P., Govindarajan U., Ramachandaramurthy V.K., Subramaniam U., Garrido S.

    Published 2023
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  13. 13
    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models

    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

    Published 2019
    “…However, the typical yields are only 50–60% of the potential, and artificial intelligence research on modelling of the crop yield and energy consumption is still at its infancy. …”
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  14. 14
    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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  15. 15
    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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  16. 16
    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.

    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…This paper presents our work on developing an intelligent system for predicting crop yield, for example oil-palm yield, from climate and plantation data. …”
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  17. 17
    Development Of Artificial Intelligence (Ai) For Image Processing And Conceptual Distance Computation From Camera For Pick And Place Of Oil Palm Fresh Fruit Bunch (Ffb)

    Development Of Artificial Intelligence (Ai) For Image Processing And Conceptual Distance Computation From Camera For Pick And Place Of Oil Palm Fresh Fruit Bunch (Ffb) by Saifuddin, Siti Adawiyyah Siddiqa

    Published 2019
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    Monograph
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  18. 18
    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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  19. 19
    Chili crop segregation system design and development strategies

    Chili crop segregation system design and development strategies by Wan Daud, Wan Mohd Bukhari, Abdul Aziz, Mohd Fareezuan, Ahmad Izzuddin, Tarmizi, Norasikin, Mohd Adili, Abdul Rasid, Ahmad Fuad, Wakhi Anuar, Nur Farah Bazilah, M. N. Sukhaimie

    Published 2021
    “…This paper focused more on the Machine Learning (ML) technique, which is the main component of Artificial Intelligence. The image data taken from chili samples can be trained by using Learning Algorithm in the MATLAB program. …”
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  20. 20
    Disease detection of solanaceous crops using deep learning for robot vision

    Disease detection of solanaceous crops using deep learning for robot vision by Ahmad Radzi, Syafeeza, A.Halim, Nurul Hidayah, Abd Razak, Norazlina, Mohd Saad, Wira Hidayat, Wong, Yan Chiew, Amsan, Azureen Naja

    Published 2022
    “…Identifying the correct diseases is crucial since it can improve the quality and quantity of crop production. With the advent of Artificial Intelligence (AI) technology, all crop-managing tasks can be automated using a robot that mimics a farmer's ability. …”
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