Optimized Captain Selection Using Diffusion-Based Player Behavior Synthesis and Multicriteria Decision Making With Intuitionistic Rough Fuzzy Under Dombi-AHP and PROMETHEE Methods by Ke Wang

“…To use the AHP approach, compute the weight vector for criteria. Then, we use our proposed approach, such as intuitionistic rough fuzzy Dombi weighted averaging (IRFDWA) operators and PROMETHEE, to rank candidates. …”
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Local Transmissibility-Based Identification of Structural Damage Utilizing Positive Learning Strategies by Oguz Gunes, Burcu Gunes

“…The numerical study shows detection accuracy above 90% with one-class support vector machine (OCSVM) and correct localization across all damage scenarios. …”
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Optimizing pore pressure prediction in earth dams through the integration of panel data and intelligent models by Behrang Beiranvand, Taher Rajaee, Mehdi Komasi

“…Abstract Modern dam safety management requires comprehensive instrumentation systems to monitor structural behavior and process critical data. Such systems play a vital role in identifying both immediate anomalies and gradual trends that may indicate potential safety hazards. …”
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Estimation of Soil Cohesion Using Machine Learning Method: A Random Forest Approach by Hai-Bang Ly, Thuy-Anh Nguyen, Binh Thai Pham

“…In this study, machine learning models, namely, support vector machine (SVM), Gaussian regression process (GPR), and random forest (RF), were built based on a data set of 145 soil samples collected from the Da Nang-Quang Ngai expressway project, Vietnam. …”
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Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction Using Biologically Inspired BWT and SVM by Nilesh Bhaskarrao Bahadure, Arun Kumar Ray, Har Pal Thethi

“…Furthermore, to improve the accuracy and quality rate of the support vector machine (SVM) based classifier, relevant features are extracted from each segmented tissue. …”
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Quantum Algorithm for Solving the Wave Equation on a Hexagonal Grid by Roman Novak

“…Numerical methods based on finite differences for solving the wave equation are prone to various errors, a challenge that also applies to the semi-discrete case of a recently proposed quantum algorithm that preserves continuous time while discretizing space into a quantum state vector. The inherent limitations of quantum processing, which affect the generality and extensibility of the quantum algorithm compared to classical numerical solvers, are offset by the logarithmic scaling of the number of qubits with the number of grid points. …”
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Performance and Improvement Analysis of the Underwater WSN Using a Diverse Routing Protocol Approach by K. Sathish, C. V. Ravikumar, Asadi Srinivasulu, A. Rajesh, Olutayo Oyeyemi Oyerinde

“…A network path is chosen to send traffic by using the routing method, a process that is also known as a protocol. The routing protocols ad-hoc on-demand distance vector (AODV), dynamic source routing (DSR), dynamic manet on demand routing protocol (DYMO), location-aided routing 1 (LAR 1), optimized link state routing (OLSR), source-tree adaptive routing optimum routing approach (STAR-ORA), zone routing protocol (ZRP), and STAR-least overhead routing approach (STAR-LORA) are a few models of routing techniques. …”
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A Novel Approach to the Sintering Schedule of Ba (Co0.7Zn0.3)1/3Nb2/3O3 Dielectric Ceramics for Microwave Applications by Mohamed Mouyane, Brahim Itaalit, Jérôme Bernard, David Houivet

“…The relationships among the heat treatment process optimization, the structural, microstructural characteristics, and the microwave dielectric properties of the BCZN ceramics were investigated using X-ray diffraction, scanning electron microscopy, energy dispersion analysis, and vector network analysis. …”
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Diabetes Mellitus Disease Prediction and Type Classification Involving Predictive Modeling Using Machine Learning Techniques and Classifiers by B. Shamreen Ahamed, Meenakshi S. Arya, S. K. B. Sangeetha, Nancy V. Auxilia Osvin

“…Various ML algorithms such as Random Forest, Light Gradient Boosting Machine, Gradient Boosting Machine, Support Vector Machine, Decision Tree, and XGBoost are being used. …”
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Anomaly-Based Intrusion Detection System in Wireless Sensor Networks Using Machine Learning Algorithms by Belal Al-Fuhaidi, Zainab Farae, Farouk Al-Fahaidy, Gawed Nagi, Abdullatif Ghallab, Abdu Alameri

“…It used different machine learning (ML) algorithms, random forest (RF), decision tree (DT), support vector machine (SVM), and K-nearest neighbors (KNNs) to analyze network traffic and binary classification or multiclass classification. …”
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Construction and application of luminescent strain of Pectobacterium carotovorum harboring luxCDABE operon by ZHONG Lingkun, XU Cuihong, HUANG Zeming, AN Qianli, LIANG Yan

“…The luxCDABE operon was cloned into the vector pBBR1MCS2, and the resulting pBBR1MCS2-luxCDABE plasmid was transformed into P. carotovorum subsp. carotovorum LMG2404, namely LMG2404-LUX. …”
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Effect of Multifactor Interaction on the Accuracy of RV Reducers by Zihui Wang, Rui Xu, Jiabao Pan, Qingqing Chen, Jing Zhang, Jiugen Wang

“…The rotary vector (RV) reducer is one of the widely used mechanical components in industrial systems, specifically in robots. …”
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Research and Application of Medium Voltage Drive System in Multi-stand Hot Continuous Rolling Finishing Mill by NAN Yonghui, ZHANG Zhe, HE Chengzhao, ZHOU Zhenbang, LIU Jianping, ZHOU Weijun

“…It mainly introduces the main circuit scheme of the mill main drive system, the control principle of the grid side converter, and the vector control principle of the motor. Causes of torsional vibration are analyzed, and the suppression method of motor torsional vibration is introduced. …”
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Enhancing Image Denoising Performance of Bidimensional Empirical Mode Decomposition by Improving the Edge Effect by Feng-Ping An, Da-Chao Lin, Xian-Wei Zhou, Zhihui Sun

“…Bidimensional empirical mode decomposition (BEMD) algorithm, with high adaptive ability, provides a suitable tool for the noisy image processing, and, however, the edge effect involved in its operation gives rise to a problem—how to obtain reliable decomposition results to effectively remove noises from the image. …”
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Differential Evolution with Novel Mutation and Adaptive Crossover Strategies for Solving Large Scale Global Optimization Problems by Ali Wagdy Mohamed, Abdulaziz S. Almazyad

“…The proposed algorithm, namely, ANDE, introduces a new triangular mutation rule based on the convex combination vector of the triplet defined by the three randomly chosen vectors and the difference vectors between the best, better, and the worst individuals among the three randomly selected vectors. …”
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Graph-based two-level indicator system construction method for smart city information security risk assessment by Li Yang, Kai Zou, Yuxuan Zou

“…For the simulation of risk level prediction, we compared our method with some machine learning algorithms, such as ridge regression, Lasso regression, support vector regression, decision trees, and multi-layer perceptron. …”
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Optimal Band Configuration for the Roof Surface Characterization Using Hyperspectral and LiDAR Imaging by Prakash Nimbalkar, Anna Jarocinska, Bogdan Zagajewski

“…The optimal bands were investigated using supervised classifiers such as artificial neural network (ANN), support vector machine (SVM), and spectral angle mapper (SAM) by comparing accuracies. …”
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Plant Classification Method Using Histogram and Machine Learning for Smart Agriculture Applications by Orhan Yaman, Türker Tuncer

“…The generated features are fed to two shallow classifiers, which are the support vector machine (SVM), and k nearest neighbor (KNN). …”
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Continuous glucose data construction and risk assessment application of diabetic retinopathy complications for patients with type 2 diabetes mellitus by Yaguang Zhang, Liansheng Liu, Hong Qiao

“…Compared with the three commonly used LSTM, GPR, and support vector machine, the proposed model can construct accurate results. …”
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HierLabelNet: A Two-Stage LLMs Framework with Data Augmentation and Label Selection for Geographic Text Classification by Zugang Chen, Le Zhao

“…Specifically, LLM-based data augmentation strategies are employed to mitigate the scarcity of labeled data and class imbalance. A semantic vector database is utilized to filter the label space prior to inference, enhancing the model’s adaptability to diverse geographic terms. …”
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