Search Results - (( initial location method algorithm ) OR ( using classification using algorithm ))

Fault diagnosis in unbalanced radial distribution networks using generalised regression neural network by Mirzaei, Maryam

“…Using the proposed method, less learning time of PNN is required for classification. …”
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An implementation of regional descriptor and line roi in development of semi-automated strabismus detection system by Zolkifli, Nur Syazlin

“…This research proposes three phases: pre-processing, feature extraction, and classification. Initially, the image in pre-processing undergoes Viola Jones algorithm, red channel extraction, contrast adjustment and median filtering to reduce the noise and enhance the image. …”
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Advances in remote sensing technology, machine learning and deep learning for marine oil spill detection, prediction and vulnerability assessment by Yekeen, S.T., Balogun, A.-L.

“…The Support Vector Machine (SVM) and Artificial Neural Network (ANN) are the most used machine learning algorithms for oil spill detection, although the restriction of ML models to feed forward image classification without support for the end-to-end trainable framework limits its accuracy. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…The classification is performed using the derived features from the thermal images and the backscatter features. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

“…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
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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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ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

“…The Information Gain algorithm is used to select the most significant permissions, then the classification algorithms Naïve Bayes, Random Forest and J48 used to classify the Android apps as botnet or benign apps. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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Development of a fingerprint gender classification algorithm using fingerprint global features by Abdullah, Siti Fairuz, Abdul Rahman, Ahmad Fadzli Nizam, Abal Abas, Zuraida, Mohd Saad, Wira Hidayat

“…This algorithm is highly recommended in extracting a fingerprint global feature for gender classification process.…”
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Enhanced cell-based algorithm with dynamic radius in solving capacitated multi-source weber problem by Nurhazwani, Ahmad Razak

“…This method was derived from previous study that divides the distribution of customers into smaller cells of promising locations. …”
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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

“…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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