Spot the bot: the inverse problems of NLP by Vasilii A. Gromov, Quynh Nhu Dang, Alexandra S. Kogan, Assel Yerbolova

“…To construct the training and test datasets, we propose to separate not the texts of bots, but bots themselves, so the test sample contains the texts of those bots (and people) that were not in the training sample. …”
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Localization algorithm for large-scale wireless sensor networks based on FCMTSR-support vector machine by Fang Zhu, Junfang Wei

“…For a large-scale wireless sensor network, localization algorithm based on support vector machine faces to the problem of the large-scale learning samples. The large-scale training samples will lead to high burden of the training calculation, over learning, and low classification accuracy. …”
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Supply chain finance credit risk assessment using support vector machine–based ensemble improved with noise elimination by Ying Liu, Lihua Huang

“…Then, we obtained the final classification results by combining finally individual prediction through AdaBoosting algorithm on the new sample set. …”
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Research on digital matching methods integrating user intent and patent technology characteristics by Jianwei Yang, Yi Wang, Bonan Zang, Min Peng, George Torrens

“…The method consists of four main steps: First, based on the Kano model, this research proposes a G-HOQ method for requirement mining, classification, and function mapping, integrating Grey Relational Analysis (GRA) and the House of Quality (HOQ). …”
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Early warning strategies for corporate operational risk: A study by an improved random forest algorithm using FCM clustering. by Xini Fang

“…Following this, the FCM clustering algorithm is utilized for pre-processing sample data to improve the efficiency and accuracy of data classification. …”
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A Resource-Efficient Multi-Entropy Fusion Method and Its Application for EEG-Based Emotion Recognition by Jiawen Li, Guanyuan Feng, Chen Ling, Ximing Ren, Xin Liu, Shuang Zhang, Leijun Wang, Yanmei Chen, Xianxian Zeng, Rongjun Chen

“…., delta, theta, alpha, beta, and gamma, from EEG signals, followed by the acquisition of multi-entropy features, including Spectral Entropy (PSDE), Singular Spectrum Entropy (SSE), Sample Entropy (SE), Fuzzy Entropy (FE), Approximation Entropy (AE), and Permutation Entropy (PE). …”
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A Multitask CNN for Near-Infrared Probe: Enhanced Real-Time Breast Cancer Imaging by Maryam Momtahen, Farid Golnaraghi

“…CNN processed data from 133 breast phantoms into 266 samples using data augmentation techniques, such as mirroring. …”
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Evaluation of Different Machine Learning Models for Predicting Soil Erosion in Tropical Sloping Lands of Northeast Vietnam by Tuan Vu Dinh, Nhat-Duc Hoang, Xuan-Linh Tran

“…This study evaluates possibility of predicting erosion status by machine learning models, including fuzzy k-nearest neighbor (FKNN), artificial neural network (ANN), support vector machine (SVM), least squares support vector machine (LSSVM), and relevance vector machine (RVM). …”
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Automatic Diagnosis of Microgrid Networks’ Power Device Faults Based on Stacked Denoising Autoencoders and Adaptive Affinity Propagation Clustering by Fan Xu, Xin Shu, Xiaodi Zhang, Bo Fan

“…Compared with other traditional cluster methods, such as the Fuzzy C-mean (FCM), Gustafson–Kessel (GK), Gath–Geva (GG), and affinity propagation (AP), clustering algorithms can identify fault samples without cluster center number selection. …”
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TWD-DepNet: a deep network enhanced by three-way decisions for EEG-based depression detection by Chunlei Shi, Shouzhu Yan, Wei He, Haiyan Wang

“…Critically, a TWD-enhanced uncertainty quantification module is introduced, where EEG samples are partitioned into positive, negative, and boundary regions via fuzzy clustering, explicitly modeling ambiguous cases. …”
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An Unsupervised Remote Sensing Image Change Detection Method Based on RVMamba and Posterior Probability Space Change Vector by Jiaxin Song, Shuwen Yang, Yikun Li, Xiaojun Li

“…Change vector analysis in posterior probability space (CVAPS) is an effective change detection (CD) framework that does not require sound radiometric correction and is robust against accumulated classification errors. Based on training samples within target images, CVAPS can generate a uniformly scaled change-magnitude map that is suitable for a global threshold. …”
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Social Media Toxic Content Filtering System using SOIR Model by Nidhi Bhandari, Rachna Navalakhe, G.L Prajapati

“…The Semantic query Optimization-based Information Retrieval (SOIR) uses Fuzzy C Means (FCM) clustering to produce a particular data structure. …”
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Extraction of Agricultural Parcels Using Vector Contour Segmentation Network with Hybrid Backbone and Multiscale Edge Feature Extraction by Feiyu Teng, Ling Wu, Shukuan Liu

“…Most of the existing agricultural parcel extraction methods comprise semantic segmentation through remote sensing images, pixel-level classification, and then vectorized raster data. However, this approach faces challenges such as internal cavities, unclosed boundaries, and fuzzy edges, which hinder the accurate extraction of complete agricultural parcels. …”
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Occurrence characteristics and utilization potential of scarce coking coal resources in Huaibei coalfield by Run ZHAN, Wenyong ZHANG, Feng HAN, Fengtang SUI, Jiayi GU, Guijian LIU, Tian ZHAO

“…The scarce coking coal is divided into three grades: Low−ash−ultra−low−sulfur coal, ultra−low−ash−low−sulfur coal, low−ash−low−sulfur coal, and low−ash−low−sulfur coal from the perspective of clean and green development.It is estimated by classification, classification and zoning that the reserved resources of shallow scarce coking coal at −1500 m are about 10.165 million tons, accounting for 78.13% of the total reserved resources in the coal field, and the resource potential is huge. …”
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Providing a model of consumer behavior in creating brand attachment with an emphasis on the packaging component of food industry companies by maziar Ghasemzadeh Sangroudi, karim hamdi, SHADAN VAHABZADEH MUNSHI

“…The sample volume is determined based on reaching theoretical saturation. …”
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The Relationship between Socioeconomic Status and Social Health of the Elderly in Tehran with a Focus on the Mediating Role of Family Social Support by Mina Inanloo, Khadijeh Safiri, Afsaneh Tavassoli

“…In this approach, the regions of Tehran were categorized into 3 groups: developed, medium, and underprivileged. This classification was based on a study titled "Ranking of Tehran Neighborhoods in Terms of Quality of Life and Prosperity Level", which employed 53 indices of quality of life and prosperity using a fuzzy TOPSIS technique. …”
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