Search Results - (( processes specification using algorithm ) OR ( data classification problems algorithm ))

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  1. 1
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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  2. 2
    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…Specifically, some selected benchmark classification problems are used. …”
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  3. 3
    Static hand gesture recognition using artificial neural network / Haitham Sabah Hasan

    Static hand gesture recognition using artificial neural network / Haitham Sabah Hasan by Hasan, Haitham Sabah

    Published 2014
    “…Artificial neural network is built for the purpose of classification by using the back- propagation learning algorithm. …”
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  4. 4
    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm

    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

    Published 2020
    “…MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. …”
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  5. 5
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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  6. 6
    Improved intrusion detection algorithm based on TLBO and GA algorithms

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…Optimization algorithms are widely used for the identification of intrusion. …”
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  7. 7
    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm

    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

    Published 2025
    “…In the second phase, the best set of features in each group is identified through the Genetic algorithm to enhance the classification process. Finally, a voting ensemble technique is applied, in which the Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Adaptive boosting (AdaBoost) models are combined. …”
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  8. 8
    Input significance analysis: Feature selection through synaptic weights manipulation for EFuNNs classifier

    Input significance analysis: Feature selection through synaptic weights manipulation for EFuNNs classifier by Hassan, Raini, Taha Alshaikhli, Imad Fakhri, Ahmad, Salmiah

    Published 2017
    “…Specifically for the classification process, Big Data can cause the classifiers to process longer than necessary, and the redundant or irrelevant data may misguide the learning classification algorithms to learn the random error or noise related to them. …”
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  9. 9
    The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems

    The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems by Atomi, Walid Hasen

    Published 2012
    “…The performance of Multi-layer Perceptron (MLP) trained with back-propagation artificial neural network (BP-ANN) method is highly influenced by the size of the data-sets and the data-preprocessing techniques used. This work analyzes the advantages of using pre-processing datasets using different techniques in order to improve the ANN convergence. …”
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  10. 10
    An ensemble of neural network and modified grey wolf optimizer for stock prediction

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…In line with the No Free Lunch theorem which suggests that no single metaheuristic is the best for all optimization problems, the search for better algorithms is still a worthy endeavour. …”
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  11. 11
    Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review

    Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review by Aliyu, R., Mokhtar, A.A., Hussin, H.

    Published 2022
    “…While the need for selecting appropriate training algorithms is seen to be significant. Interestingly, no specific method or algorithm exists for a given problem instead the solution relies on the type of data and the algorithmâ��s or methodâ��s aptitude for resolving the provided errors. …”
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  12. 12
    Automated and high accuracy out-of-hospital heart diseases early detection system

    Automated and high accuracy out-of-hospital heart diseases early detection system by Hussein, Ahmed Faeq, Hashim, Shaiful Jahari, Abdul Aziz, Ahamd Fazli, Rokhani, Fakhrul Zaman, Wan Adnan, Wan Azizun

    Published 2017
    “…The outcome of the analysis is further classified by the machine learning algorithm. Before the classification can be performed, the intelligent classifier is trained using control data that contains 52 normal and 148 patients data. …”
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  13. 13
    An enhanced gated recurrent unit with auto-encoder for solving text classification problems

    An enhanced gated recurrent unit with auto-encoder for solving text classification problems by Zulqarnain, Muhammad

    Published 2020
    “…However, GRU suffered from three major issues when it is applied for solving the text classification problems. The first drawback is the failure in data dimensionality reduction, which leads to low quality solution for the classification problems. …”
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  14. 14
    Anomaly behavior detection using flexible packet filtering and support vector machine algorithms

    Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

    Published 2016
    “…The main method is related to processing and filtering data packets using different types of packet filtering on network system and, more specifically, capturing and filtering data packets transmitted on high speed communications links for errors and attackers’ detection and signal integrity analysis. …”
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  15. 15
    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms

    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

    Published 2020
    “…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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  16. 16
    Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve higher accuracy in fall detection system

    Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig... by Harum, Norharyati, Khalil, Mohamad Kchouri, Obeid, Ali, Hazimeh, Hussein

    Published 2022
    “…However, classical SVM can neither use prior knowledge to process accurate classifications nor solve problems characterized by ambiguity. …”
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  17. 17
    An automated high-accuracy detection scheme for myocardial ischemia based on multi-lead long-interval ECG and Choi-Williams time-frequency analysis incorporating a multi-class SVM classifier

    An automated high-accuracy detection scheme for myocardial ischemia based on multi-lead long-interval ECG and Choi-Williams time-frequency analysis incorporating a multi-class SVM... by Hussein, Ahmed Faeq, Hashim, Shaiful Jahari, Rokhani, Fakhrul Zaman, Wan Adnan, Wan Azizun

    Published 2021
    “…The classification process uses the data of 92 normal and 266 patients from four different databases. …”
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  18. 18
    Autonomous tomato harvesting robotic system in greenhouses: deep learning classification

    Autonomous tomato harvesting robotic system in greenhouses: deep learning classification by Ooi, Peng Toon, Muhammad Aizzat, Zakaria, Ahmad Fakhri, Ab. Nasir, A. P. P., Abdul Majeed, Chung, Young Tan, Leonard Chong, Yew Ng

    Published 2019
    “…In this study, a new classification algorithm using deep learning specifically convolution neural network to classify the image is either a tomato or not tomato and next, the image is classified into either a ripe or unripe tomato. …”
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  19. 19
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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  20. 20
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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