Search Results - (( model selection method algorithm ) OR ( based information among algorithm ))

Time series modeling of water level at Sulaiman Station, Klang River, Malaysia by Galavi, Hadi

“…The best ARIMA model is selected based on the minimum corrected Akaike Information Criterion (AICC) statistic obtained among the several possible ARIMA models. …”
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Computational dynamic support model for social support assignments around stressed individuals among graduate students by Al-Shorman, Roqia Rateb

“…These models explain the dynamics of support seeking and provision behaviours and were evaluated using equilibria analysis and automatic logical verification approaches for 14 selected empirical cases. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…An important contribution of the proposed method is modeling of interaction in addition to relevancy and redundancy based on information-theoretic criteria for the feature selection. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Thus, proposing the method of reestimating the dropping functions in the RED algorithm. …”
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Pembangunan model regresi poisson sifar-melambung berintegrasi dalam biostatistik by Zafakali, Nur Syabiha

“…The first phase in this research is to refer to the algorithm development procedure to model the Zero-Inflated Poisson Regression method through the bootstrap method and combined with the fuzzy regression method. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

“…RBFN-DDA performs incremental learning wherein its structure expands by adding new hidden units to include new information. As such, its training can reach stability in a shorter time compared to the gradient-descent based methods. …”
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Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

“…In recent years, statistical methods and, increasingly, machine learning-based approaches have gained popularity for landslide susceptibility modeling. …”

A New Monotone Fuzzy Rule Relabeling Framework With Application to Failure Mode and Effect Analysis Methodology by Tay, Kai Meng, Pang, Lie Meng, Lim, Chee Peng, Ishibuchi, Hisao

“…In this paper, we further propose a new three-stage framework to develop a computationally efficient MFRR algorithm. The first stage determines the combinations of fuzzy rules to be relabeled by exploiting the prior information derived from a given non-monotone fuzzy rule base. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

“…The correlation-based feature selection (CFS) method was used to select representative WPD vector subset to eliminate redundancy before combining with other features. …”
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Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

“…Blind Source Separation (BSS) refers to the statistical technique of separating a mixture of underlying source signals.BSS denotes as a phenomena and separation on mixed heart-lung sound is one of its example.The challenge of this research is to separate the separate lung sound and heart sound from mixed heart-lung sound.A clear lung sound for diagnosis purpose able to be obtained after separating the mixed heart-lung sound.In biomedical field,lung information is precious due to it has been provided for respiratory diagnosis.However,the interference of heart sound towards lung sound will generate ambiguity and it will lead to drop down the accuracy of diagnosis.Thus,a clean lung sound is needed to increases the accuracy of diagnosis.One of the ways for non-invasive respiratory diagnosis for obtaining lung information is through extracting lung sound from mixed heart-lung sound by using Two-Dimensional Nonnegative Matrix Factorization (NMF2D) algorithm.This method is based on cocktail party effect in which it refers to human brain able to selectively listen to target among a cacophony of conversations and background noise and this considered as a difficult task to machine.Therefore, duplication on cocktail party effect into machine is used to separate the mixed heart-lung sound.This research presents a novel approach NMF2D algorithm in which a suitable model for signal mixture that accommodated the reverberations and nonlinearity of the signals.The objectives of this research are focusing on investigating the useful signal analysis algorithms,defining a new technique of signal separability,designing and developing novel methods for BSS. …”
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Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen by Khoo, Wooi Chen

“…The statistical and regression properties, parameter estimation, forecasting, and graphical analysis for the new model have been examined. Model selection based upon the Akaike Information Criterion has been performed. …”
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Bacterial image analysis using multi-task deep learning approaches for clinical microscopy by Chin, Shuang Yee, Jian, Dong, Khairunnisa, Hasikin, Romano, Ngui, Lai, Khin Wee, Pauline Yeoh, Shan Qing, Xiang, Wu

“…Methods Three object detection networks of DL algorithms, namely SSD-MobileNetV2, EfficientDet, and YOLOv4, were developed to automatically detect Escherichia coli (E. coli) bacteria from microscopic images. …”
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Technical efficiency performance of Malaysian public research universities: Fuzzy data envelopment analysis / Saber Abdelall Mohamed Ahmed by Saber Abdelall, Mohamed Ahmed

“…By utilizing Fuzzy DEA (FDEA) model with algorithm, this study observes the PRUMs efficiency status during the study period and the expected average efficiency for the next 2021/2022 academic year. …”
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Face recognition using local geometrical features - PCA with Euclidean classifier by Khalid, Fatimah, Tengku Sembok, Tengku Mohd, Omar, Khairuddin

“…Before doing the feature selection, we investigate automatic methods for detecting face anchor points with 412 3D-facial points of 60 individuals. …”
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Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method by Marlan Z.M., Jamaludin K.R., Harudin N.

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Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

“…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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