Search Results - (( risk estimation using algorithm ) OR ( variable extraction method algorithm ))

Credit scoring for Cooperative of financial services using logistic regression estimated by genetic algorithm by Mustafa, Mamat, Sukono, Firman, Asep, Sholahuddin

“…In this paper the analysis of credit scoring is done using logistic regression model, which is estimated using genetic algorithms. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…Further, it focuses on the development of various forms of local risk prediction models and simple heart risk scores using non-laboratory features and machine learning (ML) algorithms. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

“…The performance of the SA algorithm has been explored in terms of accuracies and estimation errors. …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

“…The proposed method benchmarked with the state-of-the-art methods and achieved comparable results. …”
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Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

“…A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. …”
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Multi road marking detection system for autonomous car using hybrid- based method by Shah, Khan Bahadur

“…Wu dataset that consist of 1208 road images, which were extracted from videos recorded around California, the proposed algorithm performed satisfactorily. …”
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ESTIMATED PROBABILITY OF THE NUMBER OF BUILDINGS DAMAGED BY THE FLOODS AND THE COST OF REPAIRS by Mohd Khairul Amri, Kamarudin, Abdul Rahman, Hasan, Fathurrahman, Lananan

“…The number of buildings damaged and risk of losses are estimated using the principle of expected value. …”
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Development of an early software project risk asssessment application using case-based reasoning / Ahmad Zaki Kamaruddin by Kamaruddin, Ahmad Zaki

“…It covers the six software project risk feature that are selected as case feature and the Nearest Neighbor algorithm that is used for similarity matching process in retrieval phase of the CBR cycle. …”
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Risk assessment for safety and health algorithm for building construction in Oman by Al-Anbari, Saud Said

“…Risk assessment matrices are widely used to evaluate risks related to such hazards. …”
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Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

“…The significant variables determined by maximum likelihood method were then estimated using the BLR method. The BLR approach via Gibbs sampler and the random walk metropolis algorithm suggests that family history of diabetes, waist circumference and the body mass index are the significant risk factors associated with the type 2 diabetes mellitus. …”
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Inertial sensor-based instrumented cane for real-time walking cane kinematics estimation by Fernandez, Ibai Gorordo, Ahmad, Siti Anom, Wada, Chikamune

“…First, the contact phase of the cane was estimated by a convolutional neural network. Next, various algorithms for the cane orientation estimation were compared and validated using an optical motion capture system. …”
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Modeling Earthquake Bond Prices with Correlated Dual Trigger Indices and the Approximate Solution Using the Monte Carlo Algorithm by Riza Andrian Ibrahim, Sukono, Herlina Napitupulu, Rose Irnawaty Ibrahim

Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

“…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. …”
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Adaptive Step Size Based Hill-Climb Search Algorithm for MPPT Control of DFIG-WECS With Reduced Power Fluctuation and Improved Tracking Performance by Uddin M.N., Amin I.K.

A novel theoretical and practical methodology for extracting the parameters of the single and double diode Photovoltaic models by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya’acob, Mohammad Effendy, Abualigah, Laith

“…However, there is no method to date that can guarantee the extracted parameter of the PV model is the most accurate one. …”
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The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers by Zhang, Xiaolei, Iqbal bin Saripan, M., Wu, Yanjun, Wang, Zhongxiao, Wen, Dong, Cao, Zhendong, Wang, Bingzhen, Xu, Shiqi, Liu, Yanli, Marhaban, Mohammad Hamiruce, Dong, Xianling

“…Conclusions: The Combat algorithm has reduced variability in radiomic features from different scanners. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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