Optimal Scheduling Strategy of Newly-Built Microgrid in Small Sample Data-Driven Mode by CHEN Shi, YANG Linsen, LIU Yihong, LUO Huan, ZANG Tianlei, ZHOU Buxiang

“…Newly built microgrids lack historical operation data, making it challenging to predict renewable power output accurately using conventional data-driven methods, which in turn affects the accuracy of scheduling plans. …”
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Finite family groups for fermionic and leptoquark mixing patterns by Jordan Bernigaud, Ivo de Medeiros Varzielas, Jim Talbert

“…Assuming experimentally interesting CKM and PMNS matrix elements, our algorithm finds an abundance of predictive non-Abelian flavour groups and therefore provides promising directions for future model building in the flavoured leptoquark space, regardless of whether the anomalous R K ∗ $$ {\mathcal{R}}_{K^{\left(\ast \right)}} $$ measurements withstand further experimental scrutiny.…”
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Study of radioactive particle tracking using MCNP-X code and artificial neural network by Roos Sophia de Freitas Dam, César Marques Salgado

“…Counts obtained by an array of detectors properly positioned around the unit will be correlated to predict the instantaneous positions occupied by the radioactive particle by means of an appropriate mathematical search location algorithm. …”
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Use artificial neural network to recommend the lumbar spinal endoscopic surgical corridor by Chien-Min Chen, Pei-Chen Chen, Ying-Chieh Chen, Guan-Chyuan Wang

“…The SHapley Additive exPlanations algorithm was utilized to explain the relative importance of each factor. …”
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Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Support Vector Machine (SVM) is a widely used algorithm for classification, valued for its flexibility with kernels that effectively handle non-linear problems and high-dimensional data. …”
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An Efficient Nonlinear Filter for Spacecraft Attitude Estimation by Bing Liu, Zhen Chen, Xiangdong Liu, Fan Yang

“…Then the local error attitude estimator is designed with constant coefficients based on the robust H2 filtering algorithm. Subsequently, the attitude predictions and the local error attitude estimations are calculated by a gyro based model and the local error attitude estimator. …”
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Fractional-Derivative Approximation of Relaxation in Complex Systems by Kin M. Li, Mihir Sen, Arturo Pacheco-Vega

“…Since the set of parameters for the model and its initial conditions are nonunique, and there are small but significant differences in the predictions from the possible models thus obtained, the SI operation is carried out via global regression of an error-cost function by a simulated annealing optimization algorithm. …”
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RSS Tracking Control for AVs Under Bayesian-Network-Based Intelligent Learning Scheme by Kun Zhang, Kezhen Han, Nanbin Zhao

“…Additionally, a critic learning optimal control algorithm is developed to determine the control law. …”
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Evaluation of Machine Learning Models for Enhancing Sustainability in Additive Manufacturing by Waqar Shehbaz, Qingjin Peng

“…The results confirm the efficacy of ML in predicting sustainability outcomes when supported by robust experimental data. …”
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Optimization of Communication Signal Adversarial Examples by Selectively Preserving Low-Frequency Components of Perturbations by Yi Zhang, Lulu Wang, Xiaolei Wang, Dianxi Shi, Jiajun Bai

“…By utilizing the binary search algorithm, which considers the inconsistency in the model’s predictions as a constraint, LFCP can be effectively identified, and the aim of minimizing perturbed distortion while maintaining ASR can be achieved. …”
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Lithium-ion battery state-of-charge estimation based on a dual extended Kalman filter and BPNN correction by Likun Xing, Liuyi Ling, Xianyuan Wu

“…A novel model-based method, using a Dual Extended Kalman Filtering algorithm (DEKF) and Back Propagation Neural Network (BPNN), is proposed to estimate and correct lithium-ion batteries. …”
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Opportunities and challenges of AI-systems in political decision-making contexts by Max Tretter

“…Furthermore, some of them have the power to carry out in-depth simulations with varying parameters, predicting the consequences of various political decisions, and thereby providing new certainties. …”
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Forecasting the Directions of the State Policy of the Region on the Basis of Cluster Analysis of Indicators of Socio-Economic Development of Its Municipalities by S. N. Borodin

“…The advantage of the proposed approach is that it identifies and predicts the problems of socio-economic development of the region, which may be hidden in the medium-term forecast of the socio-economic region. …”
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PhyIndBC: Development of a machine learning tool for screening of potential breast cancer inhibitors from phytochemicalsGitHub by Agneesh Pratim Das, Subhash M. Agarwal

“…., k-nearest neighbor (KNN), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) were combined with various molecular fingerprints (MACCS and Morgan2) to develop multiple predictive models. Among these models, the RF algorithm coupled with the MACCS fingerprint emerged as the best performing model. …”
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Application of the SARIMA-LSTM model to evaluate the effectiveness of interventions for Visceral Leishmaniasis by Mengchen Han, Chongqi Hao, Zhiyang Zhao, Peijun Zhang, Bin Wu, Lixia Qiu

“…A paired samples t-test revealed a statistically significant difference between predicted and actual case counts (t = -4.058, p < 0.001), indicating that the actual number of cases was lower than predicted. …”
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Design of a Manned-Unmanned Teaming System and Forward-Formation Control for Crevasse Detection in the Path of a Human-Driven Vehicle by Ji-Wook Kwon, Hyoujun Lee, Taeyoung Uhm, Jongdeuk Lee, Na-Hyun Lee, Young-Ho Choi

“…The stability and performance of the proposed MUM-T system, forward-formation, and motion control algorithm are validated through simulations. Especially, the forward-formation demonstrated more than an 86% improvement in predicting and mimicking the leader&#x2019;s trajectory compared to conventional formation strategies. …”
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Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism by Lahbib Naimi, El Mahi Bouziane, Lamya Benaddi, Abdeslam Jakimi, Mohamed Manaouch

“…Subsequently, a machine learning algorithm called Bagging was employed to develop a predictive model. …”
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Detection of false data injection in electric energy metering platforms using gradient lifting decision trees and MLP neural networks by Yakui Zhu, Yangrui Zhang, Chao Zhang, Bingyu Zhang, Hongying Wang, Shaokang Feng

“…The predictor was based on a gradient boosting decision tree to predict potential data injection anomalies. The discriminator used a multilayer perceptron (MLP) neural network, combined with difference analysis between the predicted and actual values, to determine false data injection. …”
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Deep learning for automated segmentation of radiation-induced changes in cerebral arteriovenous malformations following radiosurgery by Hsing-Hao Ho, Huai-Che Yang, Wen-Xiang Yang, Cheng-Chia Lee, Hsiu-Mei Wu, I-Chun Lai, Ching-Jen Chen, Syu-Jyun Peng

“…The algorithm could be used to predict the course of RICs and facilitate clinical management. …”
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Current Status and Future Potential of Machine Learning in Diagnostic Imaging of Endometriosis : A Literature Review by Palpasa Shrestha, Bibek Shrestha, Jati Shrestha, Jun Chen

“…The machine learning algorithm first computes the image characteristics deemed significant for making predictions or diagnoses about unseen images. …”
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