Search Results - (( quality classification using algorithm ) OR ( based application interface algorithm ))

VHDL modeling of EMG signal classification using artificial neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran, Ullah, Mohammad Habib

“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been used for the classification of EMG signals. …”
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Interactive Fuzzy Logic Interface for Enhanced Real-Time Water Quality Index Monitoring by Amar Lokman, Wan Zakiah Wan Ismail, Nor Azlina Ab Aziz, Anith Khairunnisa Ghazali

Development of deep learning based user-friendly interface for fruit quality detection by Mohd Ali, Maimunah, Hashim, Norhashila

“…The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. …”
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A wheelchair sitting posture detection system using pressure sensors by Mohamad Yusoff, Muhammad Annuar Alhadi, Azmi, Nur Liyana, Nordin, Nor Hidayati Diyana

“…A graphical-user interface (GUI) based application was developed using the algorithm with the highest accuracy, DT classifier, to illustrate the result of the posture classification to the wheelchair user for any posture correction to be made in case of improper sitting posture detected.…”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging by Mohd Ali, Maimunah

“…Apart from that, a graphical user interface (GUI)-based software for determination of classification accuracy and quality prediction of the fruit is developed. …”
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao by Wong , Tee Hao

“…Statistical analyses were employed to identify the most reliable quality ratings. To address dataset imbalances, Synthetic Minority Oversampling Technique was used, enhancing dataset quality before training 40 machine learning classification algorithms. …”
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Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN) by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…EMG signal based reliable and efficient hand gesture identification can help to develop good human computer interface which in turn will increase the quality of life of the disabled or aged people. …”
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Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

“…There is a need to resolve this problem for us to get good water that can be used for domestic purposes. This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

“…This finding emphasizes that Stacking with Gradient Boosting provides much better performance in water quality classification compared to other models. This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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Monitoring water quality in Pusu river using Internet of Things (IoT) and Machine Learning (ML) by Kabbashi, Nassereldeen Ahmed, Hasan, Tahsin Fuad, Alam, Md Zahangir, Saleh, Tanveer, Hassan Abdalla Hashim, Aisha

“…In addition, the application of soft computing technology for water quality assessment offers a more efficient, faster, and environmentally friendly alternative to conventional laboratory-based techniques. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…Experimental results show that the developed methods and model are able to classify the Harumanis quality with accuracy of 79% using fuzzy classification based on shape and size.…”
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Real-time power quality disturbance classification using convolutional neural networks by Husodo, Budi Yanto, Dalimi, Rinaldy, Ihsanto, Eko, Gunawan, Teddy Surya

“…Experimental results showed that the proposed algorithm produced a good result with the classification accuracy of 97.52% trained using 100 epochs. …”
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A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mohd Huzir, Siti Mariatul Hazwa, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

“…Their services are used to sniff and evaluate each agarwood to determine if it is of high quality or not. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mahabob, Noratikah Zawani, Ismail, Nurlaila, Mohd Yusoff, Zakiah, Taib, Mohd Nasir

“…So, the output was the classification of quality between low, medium low, medium high or high quality while the input was the abundances (%) of compounds. …”
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Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

“…The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions. …”
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Classification of hand gestures from EMG signals / Diaa Albitar by Albitar, Diaa

“…This study is to develop classification model to classify six hand gestures using Artificial Intelligent algorithm. …”
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