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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor
Published 2024“…These analyses provide nuanced insights into system operational dynamics and efficiency. Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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Landslide susceptibility mapping: machine and ensemble learning based on remote sensing big data
Published 2020“…Firstly, the Flexible Discriminant Analysis (FDA) supervised learning algorithm is trained for LSM and compared against other algorithms that have been widely used for the same purpose, namely Generalized Logistic Models (GLM), Boosted Regression Trees (BRT or GBM), and Random Forest (RF). …”
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Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV
Published 2018“…Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. …”
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Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image
Published 2016“…In this research, most of satisfactory results achieved from the generic model and proves it can be easily performed to different WorldView-2 images from different areas and provided the high accuracy through algorithms for tree species detection namely, Mesua Ferrea, Samanea Saman, and Casuarina Sumatrana without using any training data. …”
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Enhanced dynamic security assessment for power system under normal and fake tripping contingencies.
Published 2019“…The hybrid logistic model tree (hybrid LMT) approach proposed in this study combines the symmetrical uncertainties (SU) algorithm and the logistic model tree (LMT) algorithm. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…ANN based STLF models commonly use back-propagation algorithm, which generally exhibits a slow and improper convergence that affects the forecast accuracy. …”
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Identification of Freeform Depression Feature in a Part Using Vertex Attributes From Feature Volume / Pramod S Kataraki and Mohd Salman Abu Mansor
Published 2018“…First, the algorithm quantifies input part model’s volume and identifies the faces having depression feature. …”
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Hybrid intelligent methods for parameter identification and load frequency control in power system
Published 2014“…The accuracy of the parameter identification of power system model and efficiency of frequency control are part of the challenging work in power system operation and control area. …”
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Recommendation System Model For Decision Making in the E-Commerce Application
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…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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Fraud detection in shipping industry based on location using machine learning comparison techniques
Published 2023“…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. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…The servomotor's transfer function is obtained via system identification and is modelled using MATLAB commands. …”
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Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm
Published 2020“…The Gradient-Based Cuckoo Search (GBCS) algorithm was used to achieve the final objective. …”
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The Contribution of Feature Selection and Morphological Operation For On-Line Business System’s Image Classification
Published 2015“…It also target to study the effect of morphological operation and feature selection to the accuracy. For the classification experiment, it was tested using four types of classifiers: BayesNet, NaiveBayesUpdateable, RandomTree and IBk.…”
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Electricity distribution network for low and medium voltages based on evolutionary approach optimization
Published 2015“…This thesis proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified Minimum Spanning Tree (MST). …”
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Crown counting and mapping of missing oil palm tree using airborne imaging system
Published 2019“…This helps to facilitate semi-skillful users to implement the tree counting algorithms. Users are required to input three parameters which are, image resolution, planting distance of oil palm trees as well as the diameter of oil palm crown, in order to operate the interface. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation
Published 2021“…Firstly, a mathematical model that represented the pneumatic system was determined by system identification approach. …”
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An approach to enhance the structural operational deflection shape under random ambient excitation through mode shape expansion / Muhamad Azhan Anuar
Published 2021“…(iii) An expansion approach was applied by a linear combination of both OMA and FE mode shapes data using the modified LCP method (iv) A new algorithm that includes the selection matrix and rotation matrix were used to obtain the estimated experimental mode shape at higher DOFs. …”
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