Search Results - (( evolution classification modelling algorithm ) OR ( variable deviation selection algorithm ))

Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition by Al Jawarneh, Abdullah Suleiman Saleh

“…The penalized regularization methods are statistical techniques used to regularize and select the necessary predictor variables that have substantial effects on the response variable. …”
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

“…In this work, we will develop a robust classification model that can be utilized in cancer diagnosis using immunofingerprint data. …”
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Finding an effective classification technique to develop a software team composition model by Gilal, Abdul Rehman, Jaafar, Jafreezal, Capretz, Luiz Fernando, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin

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Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

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Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

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Fault diagnostic advisory system using moving-range chart and hazard operability study. by Heng, Han Yann, Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

“…Although the scheme was developed based on precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP study for each selected monitoring variables.…”
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Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

“…Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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Fault diagnostic advisory system using moving-range chart and hazard operability study by Heng, Han Yann, Ali, Mohamed Wijayanuddin, Kamsah, Mohd. Zaki

“…Although the scheme was developed based on precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP study for each selected monitoring variables…”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

“…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

“…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Feature selection was used to sort out key features for further classification. News classification into factors affecting stock market turning point was done using Naïve Bayes, Deep Learning, Generalized Linear Model (GLM) and Support Vector Machine (SVM). …”
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Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

“…Although the scheme was developed based on data of fatty acid precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP for each selected monitoring variables.…”
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Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models by Baba, Ishaq Abdullahi, Midi, Habshah, Leong, Wah June, Ibragimov, Gafurjan I.

“…The SIS method uses the rank correlation screening (RCS) algorithm in the pre-screening step and the traditional Pathwise coordinate descent algorithm for computing the sequence of the regularization parameters in the post screening step for onward model selection. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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ios Mobile Malware Deep Analysis And Classification For Social Media And Online Banking Exploitation by Muhammad ‘Afif Bin Husainiamer

Optimization of process parameters for rapid adsorption of Pb(II), Ni(II), and Cu(II) by magnetic/talc nanocomposite using wavelet neural network by Darajeh, Negisa, Masoumi, Hamid Reza Fard, Kalantari, Katayoon, Ahmad @ Ayob, Mansor, Shameli, Kamyar, Basri, Mahiran, Khandanlou, Roshanak

“…After minimizing this error, the topologies of the algorithms were compared based on the coefficient of determination and absolute average deviation. …”
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Optimal Reactive Power Dispatch Solution by Loss Minimization Using Moth-Flame Optimization Technique by Rebecca Ng, Shin Mei, Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Hamdan, Daniyal

“…The statisticalanalysis of this research illustrated that MFO is able to produce competitive results by yielding lowerpower loss and lower voltage deviation than the selected techniques from literature.…”
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Statistical band selection for descriptors of MBSE and MFCC-based features for accent classification of Malaysian English / Yusnita M. A. ...[et al.] by M. A., Yusnita, M. P., Paulraj, Yaacob, Sazali, A. B., Shahriman, Mokhtar, Nor Fadzilah

“…Firstly, statistical descriptors such as mean, standard deviation, kurtosis and the ratio of standard deviation to kurtosis of mel-bands spectral energy and secondly, mel-frequency cepstral coefficients were extracted from the selected bands to model an accent classifier, implemented based on neural network model and K-nearest neighbors. …”
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