2D DOA Estimation of Wideband and FH Signals Using Improved K-means Clustering and Implementation Considerations by Zahra Memarian, Mahdi Majidi

“…Additionally, a fast, modified K-means clustering algorithm is developed to refine DOA estimation for FH and WB signals across multiple active subchannels. …”
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ANFIS Models with Subtractive Clustering and Fuzzy C-Mean Clustering Techniques for Predicting Swelling Percentage of Expansive Soils by Mehdi Hashemi Jokar, Ali Heidaripanah

“…This study aims to optimize subtractive clustering and Fuzzy C-Mean Clustering (FCM) models for the most accurate prediction of swelling percentage in expansive soils. …”
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An effective Key Frame Extraction technique based on Feature Fusion and Fuzzy-C means clustering with Artificial Hummingbird by Sumandeep Kaur, Lakhwinder Kaur, Madan Lal

“…This study proposes a key frame extraction method from a video that (i) first removes insignificant frames by pre-processing, (ii) second, four visual and structural feature differences among the consecutive frames are extracted and aggregated to identify informative frames, (iii) third, to cluster the obtained frames, a hybrid FCM-AHA method is proposed by combining Fuzzy C-means(FCM) with artificial hummingbird optimization algorithm (AHA) to circumvent the local minima trapping problem of FCM, and finally, from each cluster, the two frames having greatest Euclidean distance from all the other frames within a cluster is selected as key frames to remove redundant frames. …”
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Extraction and analysis of spatial heterodyne potassium signals based on principal component analysis and non-local means method by Wang XinQiang, Yang SiQian, Xiong Wei, Wang FangYuan, Ye Song

“…Principal Component Analysis (PCA) is then applied to separate the atmospheric background from the weak potassium lamp signals in the mixed signals, followed by the introduction of the Non-Local Means (NLM) denoising algorithm to suppress noise. …”
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Improved SOR signal detection algorithm in massive MIMO-TRDMA systems by Mingyue WANG, Fangwei LI, Xiaorong JING, Haibo ZHANG, Junzhou XIONG

“…In the massive multi-input multi-output time-reversal division multiple access (MIMO-TRDMA) systems, the traditional linear minimum mean square error (MMSE) algorithm achieved approximately the best performance.However, the matrix inversion of the MMSE algorithm was too complicated to ensure real-time processing of signal detection.To solve this problem, an improved successive over-relaxation (SOR) signal detection optimization algorithm was proposed.The proposed algorithm reasonably upgraded the solution of linear equations to prevent the complicated calculation of matrix inversion.Meanwhile, the steepest descent idea was used to provide an effective search direction for the SOR signal detection algorithm, achieving a rapid convergence rate and stronger inspection performance.The simulation results show that the proposed algorithm has the similar best performance with fewer update times compared with the traditional MMSE algorithm, and the calculation complexity is reduced from O(M³)to O(²).…”
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Improved SOR signal detection algorithm in massive MIMO-TRDMA systems by Mingyue WANG, Fangwei LI, Xiaorong JING, Haibo ZHANG, Junzhou XIONG

“…In the massive multi-input multi-output time-reversal division multiple access (MIMO-TRDMA) systems, the traditional linear minimum mean square error (MMSE) algorithm achieved approximately the best performance.However, the matrix inversion of the MMSE algorithm was too complicated to ensure real-time processing of signal detection.To solve this problem, an improved successive over-relaxation (SOR) signal detection optimization algorithm was proposed.The proposed algorithm reasonably upgraded the solution of linear equations to prevent the complicated calculation of matrix inversion.Meanwhile, the steepest descent idea was used to provide an effective search direction for the SOR signal detection algorithm, achieving a rapid convergence rate and stronger inspection performance.The simulation results show that the proposed algorithm has the similar best performance with fewer update times compared with the traditional MMSE algorithm, and the calculation complexity is reduced from O(M³)to O(²).…”
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Pattern recognition in SARS cases: insights from t-SNE and k-means clustering applied to COVID-19 symptomatology by Julliana Gonçalves Marques, Bruno Motta de Carvalho, Luiz Affonso Guedes, Márjory Da Costa-Abreu

“…This study proposes a dimensionality reduction approach combined with a clustering technique to visually analyse structural similarities among SARS-infected individuals, aiming to determine whether aspects such as case progression and diagnosis impact these patterns.MethodsThis analysis utilised the t-Distributed Stochastic Neighbour Embedding (t-SNE) algorithm for dimensionality reduction, combined with Gower's distance to handle categorical data, and k-means clustering. …”
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Improved landslide susceptibility assessment: A new negative sample collection strategy and a comparative analysis of zoning methods by Jiani Wang, Yunqi Wang, Manyi Li, Zihan Qi, Cheng Li, Haimei Qi, Xiaoming Zhang

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Kombinasi K-Means dan Support Vector Machine (SVM) untuk Memprediksi Unsur Sara pada Tweet by Wiga Maulana Baihaqi, Muliasari Pinilih, Miftakhul Rohmah

“…This study aims to make sentence corpus containing SARA elements obtained from twitter, then label sentences with labels containing elements of SARA and not, and conduct group sentiments. The algorithm used for the labeling process is k-means, while Support Vector Machine (SVM) is used for the classification process. …”
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A Improving House Price Clustering Results with K-means through the Implementation of One-hot Encoding Pre-processing Technique by Vicka Rizqi Maulani, Mula Agung Barata, Pelangi Eka Yuwita

“…The 0.15 matrix result is relatively low, which is caused by the overlap of house price values in the dataset, but it has been shown that one-hot encoding can represent categorical data well in the data pre-processing process so that the data can be processed with the k-means algorithm.…”
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Using Artificial Intelligence Techniques For Intrusion Detection System by Manar Ahmed, Bayda Khaleel

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A Novel Main-Lobe Cancellation Method Based on a Single Notch Space Filter and Optimized Correlation Analysis Strategy by Jiazhi Zhang, Xin Zhang, Weibo Deng, Liang Guo, Qiang Yang

“…Then, an improved main-lobe cancellation (IMLC) method based on single notch space filter and correlation analysis is proposed to get training data which contains precise clutter information. …”
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Measurement and Modeling of Spindle Thermal Error of Fiveaxis CNC Machine Tool with Double Turntable by LIU Xianli, SONG Houwang, WU Shi, YUE Caixu, Steven Y.Liang, LI Rongyi

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Active Privacy-Preserving, Distributed Edge–Cloud Orchestration–Empowered Smart Residential Mains Energy Disaggregation in Horizontal Federated Learning by Yu-Hsiu Lin, Yung-Yao Chen, Shih-Hao Wei

“…In this study, a distributed horizontal federated learning (HFL)–based energy management framework that implements an active privacy-preserving and edge–cloud collaborative computing–based energy disaggregation algorithm for smart mains energy disaggregation to energy-efficient smart houses/buildings is proposed, and its preliminary implementation, in which active two-stage energy disaggregation considering edge–cloud collaborative computing for autonomous AI modeling is achieved under HFL preserving user data privacy, is demonstrated. …”
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Impacts of Ground Slope on Main Performance Figures of Solar Chimney Power Plants: A Comprehensive CFD Research with Experimental Validation by Erdem Cuce, Pinar Mert Cuce, Harun Sen, K. Sudhakar, Umberto Berardi, Ugur Serencam

“…In this study, the impacts of the different slope angles of the ground, where the solar radiation is absorbed through the collector, on the main performance parameters of the system are numerically analysed through a reliable CFD software ANSYS FLUENT. …”
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Algorithms and probabilistic models of parameters of operation of in-plant power supply by E. I. Gracheva, O. V. Naumov, A. N. Gorlov, Z. M. Shakurova

“…To address the problems of the functioning of the SES. To develop algorithms for evaluating the parameters of the efficiency of the functioning of the systems of intra-plant power supply. …”
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MODELING OF A DUPLEX MILLER AND CONDITIONS OF FORMATION OF TREATMENT OF WHEEL PAIRS OF MAIN ELECTRIC CARDS, DUAL CARS, ELECTRO SECTIONS by Victor Shapovalov, Alexandr Permyakov, Alexander Klochko

“…The subject matter of the research in the article is the process of restoring the quality and accuracy of the working surface of the wheelsets of the main electric locomotives, electric sections. The purpose of the work is to develop a modeling method for a special shaped cutter with increased productivity, designed to process the profile of locomotive railway wheels taking into account the shaping processes, which is based on the theory of modeling the high-speed milling process through the shaping efficiency coefficient. …”
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Evaluating Supervised Learning Classifier Performance for OFDM Communication in AWGN-Impacted Systems by Lavanya Vaishnavi D A, Anil Kumar C

“…With the obtained results we have proposed an hybrid model by implementing various ML algorithm for existing communication system pertaining to the receiver for reconstruction of the received signals by training the system using the data transmitted and received data is subjected to testing proposed ML algorithm. …”
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Discrete Starfish Optimization Algorithm for Symmetric Travelling Salesman Problem by Muhammet Aktas, Fatih Kilic

“…The Wilcoxon signed-rank test and Ablation test are applied to measure the significant difference in the values of the algorithms and to observe the performance effect of the main components used in the proposed algorithm on tour length and execution time, respectively. …”
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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…By synergistically combining K-Means Clustering with a multiple-input deep learning regression-based model (DL-KMA), we have achieved substantial improvements in altitude estimation accuracy. …”
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