Search Results - (( risk reduction using algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification by Suihai, Chen, Chih How, Bong, Po Chan, Chiu

“…However, compared with the traditional risk control algorithm (logistic regression algorithm), CatBoost algorithm also needs to have the advantages of high efficiency, low algorithm complexity and strong interpretable ability. …”
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Finger vein verification system using repeated line tracking and dimensionality reduction using PCA algorithms with SURF matching by Ei Wei., Ting, M. Z., Ibrahim, D.J., Mulvaney

“…The Speeded-Up Robust Features (SURF) Algorithms is used to determine the interest points. …”
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Backward reduction application for minimizing wind power scenarios in stochastic programming by Muhamad Razali N.M., Hashim A.H.

“…The algorithm determines a subset from the initial scenario set and assigns new probabilities to the preserved scenarios. …”

Preprocessing Noise Reduction For Assistive Listening System by Nurul, Md Yunus, Noor Aliff, Noor Affande, Roshahliza, M. Ramli, Noor, Ali O. Abid, Salina, Abdul Samad

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Modeling And Control Of V-Groove Rotary Impact Driver by Leong, Chi Hoe

“…The purpose of doing the latter is to verify the developed algorithm so that it does not have risk of overrun on defined solver fixed time step. …”
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Investigation of dimensionality reduction in a finger vein verification system by Ting, Ei Wei, M. Z., Ibrahim, Mulvaney, D. J.

“…The vein pattern was extracted using repeated line tracking and dimensionality reduction using principal components analysis to generate the feature vector. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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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

“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection by Siti, Mujilahwati, Noor Zuraidin, Mohd Safar, Ku Muhammad Naim, Ku Khalif, Nasyitah, Ghazalli

“…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. …”
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A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities by Idris, A.M., Rusli, R., Nasif, M.S., Ramli, A.F., Lim, J.S.

“…By using mixed-integer linear programming (MILP) formulation, the number of detectors needed are lower with higher risk reductions compared to the GA formulation. …”
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Classification of SNPs for obesity analysis using FARNeM modelling by Ong, Phaik Ling, Choo, Yun Huoy, Emran, Nurul Akmar

“…In this paper, we investigated feature selection process in obesity related SPNs analysis using Forward attribute reduction based on neighbourhood rough set model (FARNeM). …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. The objective of this study is to develop an accurate and efficient model capable of recognizing the presence of children in cars based on sound data. …”
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Lithium-ion battery charge equalization algorithm for electric vehicle applications by Hannan M.A., Hoque M.M., Peng S.E., Uddin M.N.

Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO) by Liew, Jia Hun

“…Our research employs Gaussian improved Particle Swarm Optimization (GiPSO), derived from modifications implemented on Particle Swarm Optimization (PSO) with Z-axis coefficient clamping and Self-Best reduction mechanism. Z-axis coefficient Clamping provides safety and reduction of drone swarm controlled by GiPSO risk, with the physical collision with the petroleum refinery exhaust. …”
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Radiation dose, cancer risk and diagnostic performance of computed tomography pulmonary angiography examination by Haspi Harun, Hanif

“…Hence, this study aims to evaluate the radiation dose, cancer risk and image diagnostic performance of CTPA examination regarding primary and secondary optimization such as iterative reconstruction (IR) algorithm, tube potential and pitch factor selection. …”
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An enhanced supplier selection model based on optimized analytic network process towards sustainable information technology outsourcing by Fusiripong, Prashaya

“…The first has nineteen (19) sustainability criteria and seven (7) risk factors. While the latter is an enhanced ANP with Firefly Algorithm (ANP-FA). …”
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CT reconstruction algorithm and low contrast detectability of phantom study: a systematic review and meta-analysis by Yusof, Nur Aimi Adibah, Abdul Karim, Muhammad Khalis, Mohd Asikin, Nursyazalina, Paiman, Suriati, Awang Kechik, Mohd Mustafa, Abd Rahman, Mohd Amiruddin, Mohd Noor, Noramaliza

“…Results: The dichotomous outcomes were chosen to represent the results in terms of risk ratio as per meta-analysis study. Notably, the noise in iterative reconstruction (IR) reduced by 24%, 33% and 36% with the use of smooth, medium and sharp filters, respectively. …”
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

“…Most of researches in IDS which use k-centroids-based clustering methods like K-means, K-medoids, Fuzzy, Hierarchical and agglomerative algorithms to baseline network traffic suffer from high false positive rate compared to signature-based IDS, simply because the nature of these algorithms risk to force some network traffic into wrong profiles depending on K number of clusters needed. …”
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Small-Scale Deep Network for DCT-Based Images Classification by Borhanuddin B., Jamil N., Chen S.D., Baharuddin M.Z., Tan K.S.Z., Ooi T.W.M.