A hybrid model based on learning automata and cuckoo search for optimizing test item selection in computerized adaptive testing by Chanjuan Jin, Weiming Pan

“…A multi-objective cuckoo search algorithm then decides the test strategy, between content coverage and level compliance. …”
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Impact of Climate Change on the Distribution of <i>Cinnamomum malabatrum</i> (Laurales—Lauraceae), a Culturally and Ecologically Important Species of Malabar, Western Ghats, India... by Mukesh Lal Das, Sarat Chandran, Sreenath Subrahmanyam

“…The predicted range shifts and contraction of suitable habitats for the species indicate significant challenges ahead, especially in the Malabar midlands and coastal plains—areas of high endemicity. …”
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Optimisation of material composition in functionally graded plates using a structure-tuned deep neural network by Ryoichi Chiba, Takuya Kishida, Ryoto Seki, Seiya Sato

“…A fully-connected NN, configured with an open-source Bayesian optimisation framework, is employed to predict the maximum in-plane thermal stress for various combinations of design variables. …”
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Nonlinear Elasto-Mammography for Characterization of Breast Tissue Properties by Z. G. Wang, Y. Liu, G. Wang, L. Z. Sun

“…The results demonstrate that the projective displacements acquired in X-ray mammography provide sufficient constitutive information of the tumor and prove the usability and robustness of the proposed method and algorithm.…”
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Balance evaluation system using wearable IMU sensing by Tiantian Wang, Minghui Liu, Benkun Bao, Senhao Zhang, Liuxin Yang, Hongbo Yang, Kai Guo, Dianhuai Meng

“…Thus, the purpose of this study is to utilize data obtained from a low-cost, portable, small-sized IMU (specifically an accelerometer) to predict indicators derived from force platform devices. …”
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A general framework for active space embedding methods with applications in quantum computing by Stefano Battaglia, Max Rossmannek, Vladimir V. Rybkin, Ivano Tavernelli, Jürg Hutter

“…The application of this scheme to study localized electronic states in materials is showcased through the accurate prediction of the optical properties of the neutral oxygen vacancy in magnesium oxide (MgO). …”
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Safe and Robust Binary Classification and Fault Detection Using Reinforcement Learning by Josh Netter, Kyriakos G. Vamvoudakis, Timothy F. Walsh, Jaideep Ray

“…In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. …”
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Encryption–decryption-based state estimation for nonlinear complex networks subject to coupled perturbation by Peixia Gao, Chaoqing Jia, Aozhan Zhou

“…Furthermore, a uniformly bounded condition is elaborated to evaluate the algorithm performance of EDBSE. Finally, an illustrative example is conducted to verify the validity of the introduced EDBSE method.…”
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State of Health Estimation of Lithium-Ion Batteries Using Fusion Health Indicator by PSO-ELM Model by Jun Chen, Yan Liu, Jun Yong, Cheng Yang, Liqin Yan, Yanping Zheng

“…This optimization enhances the ELM’s performance, addressing instability issues in the standard algorithm. The proposed PSO-ELM model demonstrates superior accuracy in SOH prediction compared with ELM and other methods. …”
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Grade Identification of Raw Nongxiangxing Baijiu Based on Fused Data of Near Infrared Spectroscopy and Gas Chromatography-Mass Spectrometry by ZHANG Wei, ZHANG Guiyu, TUO Xianguo, FU Ni, LI Xiaoping, PANG Tingting, LIU Kecai

“…The results showed that the prediction accuracy of the model based on the spectral feature variables selected by CARS was 89.66%, the prediction accuracy of the model based on KC after feature selection was 94.83%, and the classification accuracy of the model based on the fused data of CARS + KC reached as high as 98.28%. …”
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Auxiliary Diagnosis of Breast Cancer Based on Machine Learning and Hybrid Strategy by Hua Chen, Kehui Mei, Yuan Zhou, Nan Wang, Guangxing Cai

“…Finally, five different machine learning models are used for classification prediction, the best combination of parameters for each model is found using a grid search method, and the final results of each model are derived using a 10-fold cross-validation method. …”
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Collaborative Planning for Distribution Network and PV-ESS in the Marketization Environment by Ping RAO, Yue XIANG, Haotian YAO, Youbo LIU, Junyong LIU

“…Firstly, the benefit coupling model for the subjects in the planning layer was constructed considering photovoltaic prediction errors and agency costs based on the agency transaction mode. …”
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Integrating Proximal and Remote Sensing with Machine Learning for Pasture Biomass Estimation by Bernardo Cândido, Ushasree Mindala, Hamid Ebrahimy, Zhou Zhang, Robert Kallenbach

“…We applied the Boruta algorithm for feature selection to identify influential biophysical predictors and evaluated four machine learning models—Linear Regression, Decision Tree, Random Forest, and XGBoost—for biomass prediction. …”
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A Joint Optimization Model for Energy and Reserve Capacity Scheduling With the Integration of Variable Energy Resources by M. Wajahat Hassan, Thamer Alquthami, Ahmad H. Milyani, Ashfaq Ahmad, Muhammad Babar Rasheed

“…First, the load demand is predicted through a convolutional neural network (CNN) by taking the ISO-NECA hourly real-time data. …”
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Catatonia in anti-NMDA receptor encephalitis: a case series and approach to improve outcomes with electroconvulsive therapy by F. Gabriela Kraiter, Dakota T. May, Ryan D. Slauer, Nandini Abburi, Christopher Eckstein, Suma Shah, Jonathan R. Komisar, Jacob P. Feigal

“…Patients received an average of 29.9 ECT treatments in total.Conclusions Based on clinical prediction scores, this cohort had better than expected functional outcomes. …”
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Device Modeling Based on Cost-Sensitive Densely Connected Deep Neural Networks by Xiaoying Tang, Zhiqiang Li, Lang Zeng, Hongwei Zhou, Xiaoxu Cheng, Zhenjie Yao

“…By incorporating cost-sensitive learning methods, the proposed model focus more on the critical data that determines device characteristics, leading to accurate prediction of key device characteristics under various parameters. …”
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Vulnerability of peatland fires in bengkalis regency during the ENSO El nino phase using a machine learning approach by Fauziah, Lilik B. Prasetyo, Nonon Saribanon, Nur Hayati

“…The best model is RF that was able to predict peatland fires in Bengkalis Regency effectively, with achieving an AUC value of 0.972. …”
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The authentication of Yanchi tan lamb based on lipidomic combined with particle swarm optimization-back propagation neural network by Qi Yang, Dequan Zhang, Chongxin Liu, Le Xu, Shaobo Li, Xiaochun Zheng, Li Chen

“…The results showed that particle swarm optimization-back propagation (PSO-BP) neural network had the best prediction effect, with 100 % prediction accuracy in both the training and test sets. …”
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Intelligent Methods of Operational Response to Accidents in Urban Water Supply Systems Based on LSTM Neural Network Models by Aliaksey A. Kapanski, Nadezeya V. Hruntovich, Roman V. Klyuev, Aleksandr E. Boltrushevich, Svetlana N. Sorokova, Egor A. Efremenkov, Anton Y. Demin, Nikita V. Martyushev

“…The objective of this study was to evaluate the effectiveness of LSTM models for pressure prediction tasks. To acquire real-time pressure data, an information system based on Internet of Things (IoT) technology using the MQTT protocol was proposed. …”
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Enhancing students performance through dynamic personalized learning path using ant colony and item response theory (ACOIRT) by Imamah, Umi Laili Yuhana, Arif Djunaidy, Mauridhi Hery Purnomo

“…We combined the ant colony algorithm (ACO) with Item Response Theory (IRT) to address this issue. …”
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