Search Results - adaptive k different ((estimation algorithm) OR (extraction algorithm))

Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…Consequently, the proposed adaptive feature extraction technique and neighborhood-based classifier family are tightly integrated in an adaptive K-nearest neighbor classifier.…”
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Fractional chaos maps with flower pollination algorithm for chaotic systems� parameters identification by Yousri D., Allam D., Babu T.S., AbdelAty A.M., Radwan A.G., Ramachandaramurthy V.K., Eteiba M.B.

Apply and optimize machine learning algorithms for estimating battery health by Chin, Wai Yee

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Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification by Kamarudin, Noraziahtulhidayu, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Abushariah, Mohammad A. M., Hashim, Shaiful Jahari, Hassan Azhari, Abd Rauf

“…In order to conduct the AEC, three adaptive algorithms known as affine projection (AP), least mean square (LMS), and recursive least squares (RLS) are used during the preprocessing phase. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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Acoustic echo cancellation using adaptive filter for Quranic accent signals by Kamarudin, Noraziahtulhidayu, Al Haddad, Syed Abdul Rahman, Basiron, Azli, Hassan Azhari, Rauf

“…AP indicates 93.9% for all of the classification algorithm in used, while for LMS and RLS the results are differed varies on different pattern classification algorithm stated whereby with LMS and PPCA classification, 96.9 % for accuracy and 84.8% accuracy for LMS and KNN. …”
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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.

EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

“…Throughout this research study, models like Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Adaptive Boosting (AdaBoost) will be explored. …”
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Face recognition for varying illumination and different optical zoom using a combination of binary and geometric features by Khalid, Fatimah, Amjeed, Noor, O.K. Wirza, Rahmita Wirza, Madzin, Hizmawati, Azizan, Illiana

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COMPUTER AIDED SYSTEM FOR BREAST CANCER DIAGNOSIS USING CURVELET TRANSFORM by MOHAMED ELTOUKHY, MOHAMED MESELHY

“…We started this study by developing a diagnosis system. Five feature extraction methods were developed with curvelet and wavelet coefficients to differentiate between different breast cancer classes. …”
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Advancing Predictive Maintenance: Median-Based Particle Filtering in MOSFET Prognostics by Hadi E.F., Baharuddin M.Z.B., Zuhdi A.W.M.

“…The model used a genetic algorithm to control when and how many particles were adaptively resampled applying different weighted strategies (mean or median) in response of the stochastic system deterioration. …”

Adaptive resonance theory-based hand movement classification for myoelectric control system by Fariman, Hessam Jahani

“…Five distinct hand movements are classified with an Adaptive Resonance Theory (ART) based neural network implemented, as it uses a combination of features extracted from four EMG signals. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…Firstly, data augmentation is employed in the preprocessing stage to increase the diversity of training samples, thereby improving the model’s robustness and generalization capability. The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
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Performance Modeling And Size Optimization Of A Standalone Photovoltaic System by Abdul Qayoom, Jakhrani

“…The adapted global radiation model is different from available models as it incorporates the site specific and environmnetal parameters, which considered as influential input variables. …”
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Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman by Osman, Noor Diyana

“…The missing projection data due to metal region is detected and extracted using an improved technique of dual-step adaptive thresholding. …”
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Techno-economic evaluation of off-grid hybrid renewable energy system for rural resort electrification in Malaysia / Monowar Hossain by Monowar, Hossain

“…Hybrid Optimization Model for Electric Renewable (HOMER) software is used for economic and technical analysis of the proposed hybrid renewable energy system. The estimated peak and average load per day for the resort are 1,185 kW and 13,048 kW respectively. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

“…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
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A novel AI-driven EEG images emotion recognition generalized classification model for cross-subject analysis by Li, Jingjing, Lee, Ching Hung, Duan, Dingna, Zhou, Yanhong, Xie, Xueguang, Wan, Xianglong, Liu, Tiange, Li, Danyang, Yu, Hao, Hasan, W. Z.W., Song, Haiqing, Wen, Dong

“…The SCTMSA model includes three primary components: (1) A Siamese subnet with a shared convolutional structure for extracting similarity features. (2) A transformer module with dual-head self-attention to capture global dependencies. (3) Based on traditional hard-assignment k-means clustering, we introduce a learnable soft-assignment mechanism and dynamic centroid updating strategy to achieve adaptive low-dimensional compression of the feature space. …”
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