Forecasting Renewable energy and electricity consumption using evolutionary hyperheuristic algorithm by Yang Cao, Jun Yu, Rui Zhong, Masaharu Munetomo

“…The GA continuously finds the best hyperparameters for PSO and BA based on prediction accuracy, which significantly accelerates the optimization and improves the accuracy. …”
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Edge-of-Chaos and Chaotic Dynamics in Resistor-Inductor-Diode-Based Reservoir Computing by A. H. Abbas, Hend Abdel-Ghani, Ivan S. Maksymov

“…In this paper, we suggest and theoretically validate a technically simple RLD circuit that implements a reservoir computing (RC) architecture optimized to predict the future evolution of highly nonlinear and chaotic time series. …”
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Estimation of stepwise crack propagation in ceramic laminates with strong interfaces by L. Náhlík, K. Štegnerová, P. Hutar

“…Presented approach contributes to the better understanding of the toughening mechanism of ceramic laminates and can be advantageously used for design of new layered ceramic composites and for better prediction of their failure.…”
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Artificial intelligence across oncology specialties: current applications and emerging tools by Frank Lin, Tim Rattay, John Kang, Evangelia Katsoulakis, Kyle Lafata, Ellen Kim, Christopher Yao, Harsha Nori, Christoph Ilsuk Lee

“…Artificial intelligence (AI) provides a solution to ingest and digest this data deluge to improve detection, prediction and skill development. In this review, we provide multidisciplinary perspectives on oncology applications touched by AI—imaging, pathology, patient triage, radiotherapy, genomics-driven therapy and surgery—and integration with existing tools—natural language processing, digital twins and clinical informatics.…”
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Demonstration of Emulator-Based Bayesian Calibration of Safety Analysis Codes: Theory and Formulation by Joseph P. Yurko, Jacopo Buongiorno, Robert Youngblood

“…The key innovation has come from development of code surrogate model (or code emulator) construction and prediction algorithms. Use of a fast emulator makes the calibration processes used here with Markov Chain Monte Carlo (MCMC) sampling feasible. …”
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Digital twin-driven vibration state monitoring method for gear transmission systems by TANG Xianju, HU Zhi’an, SHE Yixi, HAN Bing, SHI Zhenfu

“…This study provides valuable data support for the fatigue life prediction and reliability assessment of key components in the gearbox, contributing to the advancement of digital twin technology in the monitoring of rotating machinery.…”
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Modeling the Curb Parking Price in Urban Center District of China Using TSM-RAM Approach by Yan Wan, Jibiao Zhou, Wenqiang He, Changxi Ma

“…The results showed that TSM and RAM can account for common urban curb parking prices. The prediction results showed that the CPP is affected by the number of urban dwellers (UD), the prevalence of car ownership (CO), and the per capita disposable income (PCDI) of urban residents; the CPP can be predicted by a model built on the basis of the above three influencing factors. …”
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Comparison of Two Mechanics-Based Methods for Simplified Structural Analysis in Vulnerability Assessment by H. Crowley, B. Borzi, R. Pinho, M. Colombi, M. Onida

“…Analytical vulnerability assessment methods should ideally be validated or verified by comparing their damage predictions with actual observed damage data. However, there are a number of difficulties related to the comparison of analytical damage predictions with observed damage; for example, there are large uncertainties related to the prediction of the ground motions to which the damaged buildings have been subjected. …”
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Description-based Post-hoc Explanation for Twitter List Recommendations by Havva Alizadeh Noughabi, Behshid Behkamal, Mohsen Kahani

“…Twitter List recommender systems can generate highly accurate recommendations, but since they employ heterogeneous information of users and Lists and apply complex prediction models, they cannot provide easy understandable intrinsic explanations. …”
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Recent advances in deep learning and language models for studying the microbiome by Binghao Yan, Yunbi Nam, Lingyao Li, Rebecca A. Deek, Hongzhe Li, Siyuan Ma

“…We also discuss applications such as novel viromics language modeling, biosynthetic gene cluster prediction, and knowledge integration for metagenomics studies.…”
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Numerical Simulation of Ice Crystal Supercooled Droplet Mixed Phase Icing Based on the Improved Messinger Model by Zhengzhi Wang, Wei Zhong, Chunfu Liu, Huanyu Zhao, Senyun Liu

“…The thermodynamic process of the water film after the ice crystals impact on the surface determines the final ice shape, which is an important part of the accurate prediction of aircraft icing. In this paper, a thermodynamic model of ice crystal supercooled droplet mixed phase icing is proposed based on the extended Messinger model, according to the results of flow field and particle trajectory calculations. …”
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Utilizing the Novel Developed MLP Techniques to Survey Pile Subsidence via Optimization Algorithms by Augustinus Sieck, Graciela Daniels

“…The measured range of piles movement was from 4.5 to 20 centimeters, which predicted settlements showed us an average one percent change compared to measured magnitudes.…”
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Finding Genetic Risk Factors of Gestational Diabetes by Soo Heon Kwak, Hak C. Jang, Kyong Soo Park

“…It would be important to know whether genetic information revealed from these studies could improve our prediction of GDM and the future development of T2DM. …”
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Measured Analysis on Surface Deformation and Influence of Cutter Torque for Twin Shield Tunnelling in Silty Sand by Yuqing Dong, Zhi Ding, Yexiang Jiang, Chunlai Chen, Wenming Shen, Yinze Wang

“…The twin-line Peck formula is suitable in silty sand, but the prediction of the latter line using this formula is slightly deviated because of the secondary disturbance effect. …”
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3D landmark‐based face restoration for recognition using variational autoencoder and triplet loss by Sahil Sharma, Vijay Kumar

“…These trained embeddings are used in support vector machine for prediction. The proposed framework is compared with recently developed face recognition techniques in terms of computational time. …”
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Simulating Crowd Evacuation in a Social Force Model with Iterative Extended State Observer by Juan Wei, Wenjie Fan, Zhongyu Li, Yangyong Guo, Yuanyuan Fang, Jierui Wang

“…The information from previous process can be used to modify the current evacuation control information to achieve a better evacuation effect, and iterative learning control can achieve an effective prediction of the expected path within a limited running time. …”
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Process Optimization for Development of Guar Gum-Based Biodegradable Hydrogel Film Using Response Surface Methodology by Junaid Aman, Navin Chandra Shahi, Umesh Chandra Lohani, Divya Balodhi, Rajat Singh, Naveen Kumar, Mohd Ishfaq Bhat, Avvaru Praveen Kumar

“…The results showed significant effects on all the abovementioned parameters, and it was observed that the developed model was accurate, with a prediction error of only −3.19 to 2.99%. The optimized formulation for the preparation of hydrogel film was 0.15% initiator, 0.02% crosslinker, and 2.88% plasticizer exhibiting satisfactory biodegradability, color difference, hardness, swelling index, and transparency. …”
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Investigation of ΔE Effect on Vibrational Behavior of Giant Magnetostrictive Transducers by M. Sheykholeslami, Y. Hojjat, M. Ghodsi, K. Kakavand, S. Cinquemani

“…Results of resonance frequency prediction have been validated with experiments and good agreement has been seen.…”
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Impacts of Land Use and Land Cover Change on Soil Erosion and Hydrological Responses in Ethiopia by Ajanaw Negese

“…Future research works should pay more attention to the investigation of the impacts of land use and land cover change on groundwater hydrology and the prediction of future soil loss and hydrological imbalance under the changing land use and land cover in the country since little information is available from past researches on these issues. …”
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The Construction of Corporate Financial Management Risk Model Based on XGBoost Algorithm by Rongyuan Qin

“…The research results show that the XGBoost model selected in this paper has high reliability in predicting the financial risk assessment of enterprises, and the prediction errors are all within 3%. …”
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