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Landslide risk zoning using support vector machine algorithm
Published 2024“…The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…Additionally, the effect of signal weighting function is investigated further using multiple K values of K nearest neighbour (KNN) algorithm. …”
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Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani
Published 2016“…To evaluate the algorithm, we conducted two experiments. In the first experiment, we examine the functionality of the system, whether the system is able to identify the summarizing strategies used by students in summary writing. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The neural network methods use a number of heuristics to find appropriate parametric values. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…F-Km is found to be more accurate, time savvy and robust than standard K-means and K-means + +. Therefore, the method can be reliably used for observing tool wear state recognition without training and equivocate traditional direct tool wear.…”
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Improving Brain MR Image Classification for Tumor Segmentation using Phase Congruency
Published 2018“…Aims: This research aims to improve automated brain MR image classification and tumor segmentation using phase congruency. Methods: The skull part is removed from brain MR image by applying converging square algorithm and phase congruency based edge detection method. …”
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Development of sorting system for oil palm in vitro shoots using machine vision approach
Published 2014“…Ultimately, the sorting algorithm performance came to be evaluated by support vector machine algorithm. …”
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Feature extraction of power disturbance signal using time frequency analysis
Published 2006“…As a conclusion, SVD and PCA are useful to apply in TFD to extract important feature vectors then MMC can measure the distance metric between those mean vectors. …”
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Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework
Published 2024“…The accuracy of the prediction was controlled using the root-mean-square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2). …”
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Quasi-Newton type method via weak secant equations for unconstrained optimization
Published 2021“…The possible variants of matrix free quasi-Newton methods are further explored, using the weak secant equation. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Error concealment technique using wavelet neural network for wireless transmitted digital images
Published 2012“…The neural network architecture that can be used to implement a nonlinear vector predictor, including a multilayer perceptron (MLP), and a radial basis function network. …”
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