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Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm by Abdulwahid S., Mahmoud M.A., Abdulwahid N.

Improved random forest for feature selection in writer identification by Sukor, Nooraziera Akmal

“…Discretization process was proven to increase the classification performances and improved the identification performance in WI. An algorithm and framework of Improved Random Forest (IRF) tree was applied for feature selection process. …”
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Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Crown counting and mapping of missing oil palm tree using airborne imaging system by Kee, Ya Wern

“…A graphical user interface by using MATLAB language was created based on the best executed method to aid users in counting the trees automatically. This helps to facilitate semi-skillful users to implement the tree counting algorithms. …”
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Data mining approach to herbs classification by Ahmad Dali, Adillah Dayana, Omar, Nurul Aswa, Mustapha, Aida

“…This research performs identification and classification of herbs based on image capture ad variety of classification algorithms such as an Artificial Neural Network (ANN), K-Nearest Neighbors (IBK), Decision Table (DT) and M5P Tree algorithms. …”
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Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

“…Modelling of trees has attracted scientific research in various fields and disciplines since trees and forests play very important roles in the global system. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

“…To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection systems. …”
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Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

“…The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

“…The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Landslide susceptibility mapping: machine and ensemble learning based on remote sensing big data by Kalantar, Bahareh, Ueda, Naonori, Saeidi, Vahideh, Ahmadi, Kourosh, Abdul Halin, Alfian, Shabani, Farzin

“…Next, an ensemble model consisting of all four algorithms is implemented to examine possible performance improvements. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

“…The primary aims of this study encompass the improvement of cost estimation precision, the identification of pivotal factors that impact project costs, and the implementation of strategies aimed at reducing costs. …”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

“…Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
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Artificial intelligence for spectral classification to identify the basal stem rot disease in oil palm using dielectric spectroscopy measurements by Khaled, Alfadhl Yahya, Abd Aziz, Samsuzana, Bejo, Siti Khairunniza, Mat Nawi, Nazmi, Abu Seman, Idris

“…This study investigated the feasibility of applying genetic algorithm (GA) as a feature selection algorithm to select the most significant frequencies of dielectric spectral data for identifying BSR disease in oil palms. …”
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Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

“…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Species distribution and molecular variations in drogonflies (order: odonata) within the state of Selangor, Malaysia / Noorhidayah Binti Mamat by Noorhidayah, Mamat

“…This was supported by the higher indices of richness (R) diversity (H’) and evenness (E) for TLR. The phylogenetic trees were constructed from 40 samples using the neighbor joining (NJ) and maximum parsimony (MP) algorithms which were implemented by MEGA 4.0.2. …”
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Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation by Pande C.B., Srivastava A., Moharir K.N., Radwan N., Mohd Sidek L., Alshehri F., Pal S.C., Tolche A.D., Zhran M.