Search Results - (( regional distribution new algorithm ) OR ( parameters variation tree algorithm ))

Decision tree method for fault causes classification based on RMS-DWT analysis in 275 kV transmission lines network by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ungku Amirulddin Al Amin, Ungku Anisa, Ab Kadir, Mohd Zainal Abidin

“…The proposed method was carried out in the MATLAB/SIMULINK programming platform based upon the information made with the fault analysis of the 275 kV sample transmission line considering wide variations in the operating conditions. The classifier performance of different parameters was also compared in a confusion matrix form to obtain the best classification results of the decision tree.…”
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Decision tree method for fault causes classification based on rms-dwt analysis in 275 kv transmission lines network by Asman S.H., Aziz N.F.A., Amirulddin U.A.U., Kadir M.Z.A.A.

“…The proposed algorithm is based upon the root mean square (RMS) current duration, voltage dip, and discrete wavelet transform (DWT) measured at the sending end of a line and the decision tree method, a commonly accessible measurable method. …”

Expression invariant face recognition using multi-stage 3D face fitting with 3D morphable face model by Alomari, Abdallah A., Khalid, Fatimah, O. K. Rahmat, Rahmita Wirza, Abdullah, Muhamad Taufik

“…This proposed model will show good results when shape, texture and extrinsic variations occur in the 3D domain since the combination of multistage fitting algorithm and tree model can enhance the speed and accuracy of the system recognition capabilities. …”
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Characterisation of pineapple cultivars under different storage conditions using infrared thermal imaging coupled with machine learning algorithms by Mohd Ali, Maimunah, Hashim, Norhashila, Abd Aziz, Samsuzana, Lasekan, Ola

“…A total of 14 features from the thermal images were obtained to determine the variation in terms of image parameters among the different pineapple cultivars. …”
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A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Wendy Ling, Shinyie, Tan Lit, Ken

“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Zun, Liang Chuan, Wan Yusof, Wan Nur Syahidah, Senawi, Azlyna, Mohd Akramin, Mohd Romlay, Soo, Fen Fam, Wendy, Ling Shinyie, Tan, Lit Ken

“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

“…In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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A New Algorithm For Assessing The Xco2 Over Peninsular Malaysia Based On Gosat Data by Sim , Chong Keat

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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Shinyie, Wendy Ling, Ken, Tan Lit

“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution by Nokhanji, Nooshin

“…Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. …”
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An attack proof intelligent digital watermarking based on safe region of fast fourier transform by Olanrewaju, Rashidah Funke, Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Aburas, A. A.

“…Keywords: (Artificial Neural Network, Back Propagation algorithm, Fast Fourier Transform, FFT, Image watermarking, Safe Region,) …”
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A PSO inspired asynchronous cooperative distributed hyper-heuristic for course timetabling problems by Joe Henry Obit, Rayner Alfred, Mansour Hassani Abdalla

“…From the experimental results, it shows that the proposed Asynchronous Cooperative Distribute Low-level heuristics (ACDLLHs) algorithm is able to find new best solutions for all five medium problem instances and shared optimal solutions for all five small instances. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition by Kasim, Nur Adilla, Nuawi, Mohd Zaki, Abdul Ghani, Jaharah, Ngatiman, Nor Azazi, Che Haron, Che Hassan, Muhammad Rizal

“…The clustering system adopted a new calculation of initial centroids has successfully determined the three regions for only a single assignment and achieving the optimal distance squared through eight given data sets. …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

“…The Random Tree standalone ML-AP relay model presented the best performing models from the ML-APS relay model with the best average performance for the correctly classified fault types of 97.61 % at 5 % significance level above other ML algorithms. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi by Sherksi, Nasereddin Ibrahim

“…All water distribution networks suffer from leaks and the amount of leakage widely varies between countries and regions within a country. …”
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Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach by Shabbir Ahmed, Omar, Syed Mohamed Ali, Jaffar, Aabid, Abdul, Hrairi, Meftah, Mohd Yatim, Norfazrina Hayati

“…Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…The proposed model has distributed and cooperative hierarchical architecture, where nodes communicate with their region gateway node to make decisions. …”
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Defect detection based on extreme edge of defective region histogram by Wakaf, Zouhir, Jalab, Hamid Abdullah

“…Furthermore, Otsu-revised methods, like the valley-emphasis method and the background histogram mode extents, which overcome the drawbacks of the Otsu method, require preprocessing steps and fail to use the general threshold for multimodal defects. This study proposes a new automatic thresholding algorithm based on the acquisition of the defective region histogram and the selection of its extreme edge as the threshold value to segment all defective objects in the foreground from the image background. …”
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Acltshe-Amts: A New Adaptive Brain Tumour Enhancement And Segmentation Approaches by Alkhafaji, Ali Fawzi Mohammed Ali

“…The AMTS approach segments and extracts the whole tumor, core tumor, and enhanced tumor regions from the brain MR images, integrating the Multi-Objective Grasshopper Optimization algorithm, Kapur Entropy, Cross-Entropy, and Localized active contour.…”
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