A method for measuring carbon emissions from power plants using a CNN-LSTM-Attention model with Bayesian optimization by Jiacheng Chen, Li Zheng, Wenyan Che, Li Liu, Hui Huang, Jun Liu, Chang Xing, Penghua Qiu

“…The results indicate that the proposed model achieved the highest performance across every evaluation index for predicting CO2 emissions from coalfired power plants, and the prediction accuracy of the CO2 emission in the future months is also guaranteed.…”
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Artificial Neural Network Approach to Study Imprecisely Defined Nonlinear Systems With Case Studies by Lakshmi Durga Pathipati, Sukanta Nayak

“…A feed-forward neural network (FFNN) is used to generate outputs based on initial guesses for the field variables, and the ANN-LM algorithm optimizes the solution by minimizing the error between predicted and target values. …”
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Cooperative UAV Scheduling for Power Grid Deicing Using Fuzzy Learning and Evolutionary Optimization by Yu-Jun Zheng, Zhi-Yuan Zhang, Jia-Yu Yan, Wei-Guo Sheng

“…The algorithm is fully parallelizable and therefore can solve the problem very efficiently based on GPU parallel acceleration. …”
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Gestational diabetes mellitus and obesity: effects on offspring by O. V. Rozhkova, O. V. Remneva, N. I. Fadeeva, Yu. V. Korenovskiy, S. D. Yavorskaya

“…CHAID method (Chi Squared Automatic Interaction Detection) was used to create an algorithm for predicting adverse perinatal outcomes in GDМ. …”
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Intrusion detection system based on machine learning using least square support vector machine by Pratik Waghmode, Manideep Kanumuri, Hosam El-Ocla, Tanner Boyle

“…This framework utilizes quantum-inspired least square support vector machine (LS-SVM) classifier. This algorithm is used to enhance the classification accuracy in terms of reducing false predictions while minimizing the training time. …”
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A simulated annealing with graph-based search for the social-distancing problem in enclosed areas during pandemics. by Bayram Dundar

“…A greedy random-based algorithm is presented to determine efficiently an initial feasible solution. …”
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Artificial Neural Network Modeling of NixMnxOx based Thermistor for Predicative Synthesis and Characterization by T.D. Dongale, K.G. Kharade, N.B. Mullani, G.M. Naik, R.K. Kamat

“…The accomplished ANN modeling evidences a lower number of hidden neuron architecture exhibiting optimum performance as regards to prediction accuracy. The lower number of hidden neurons signifies a lesser amount of memory required for prediction of different chemical composition. …”
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Interpretable Machine Learning for Thermospheric Mass Density Modeling Using GRACE/GRACE‐FO Satellite Data by Qian Pan, Chao Xiong, ShunZu Gao, Zhou Chen, Artem Smirnov, Chunyu Xu, Yuyang Huang

“…A critical aspect of our work is minimizing the number of input parameters while maintaining high prediction accuracy. And the interpretability analysis of the input parameters using the Shapley additive explanation algorithm has been applied, revealing that the altitude, solar activity index P10.7 and solar zenith angle are the three most influential parameters affecting TMD variations at GRACE satellite. …”
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Efficient Resources Provisioning Based on Load Forecasting in Cloud by Rongdong Hu, Jingfei Jiang, Guangming Liu, Lixin Wang

“…It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. …”
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An Adaptive Robust Event-Triggered Variational Bayesian Filtering Method with Heavy-Tailed Noise by Di Deng, Peng Yi, Junlin Xiong

“…The one-step state prediction probability density function and the measurement likelihood function are modeled as Student’s t-distributions. …”
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Arctic Heatwaves Could Significantly Influence the Isoprene Emissions From Shrubs by Hui Wang, Allison Welch, Sanjeevi Nagalingam, Christopher Leong, Pitchayawee Kittitananuvong, Kelley C. Barsanti, Rebecca J. Sheesley, Claudia I. Czimczik, Alex B. Guenther

“…With a modified algorithm from this study, MEGAN predicts 66% higher isoprene emissions for Arctic willows during an Arctic heatwave. …”
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A recurrent neural network‐based rotor displacement estimation method for eight‐pole active magnetic bearing by Longyuan Fan, Zicheng Liu, Haijiao Wang, Dong Jiang, Yu Chen

“…The input dimensions and the architecture of the neural network are optimised to improve both prediction accuracy and computational complexity. Experimental results validate the effectiveness of the algorithm and demonstrate that the proposed method has high accuracy, robustness and generalisation ability.…”
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Investigation of Vessel Manoeuvring Abilities in Shallow Depths by Applying Neural Networks by Lúcia Moreira, C. Guedes Soares

“…The outcomes achieved with the proposed system have shown excellent accuracy and ability in predicting ship manoeuvring with varying depths of shallow water.…”
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Systematic, computational discovery of multicomponent and one-pot reactions by Rafał Roszak, Louis Gadina, Agnieszka Wołos, Ahmad Makkawi, Barbara Mikulak-Klucznik, Yasemin Bilgi, Karol Molga, Patrycja Gołębiowska, Oskar Popik, Tomasz Klucznik, Sara Szymkuć, Martyna Moskal, Sebastian Baś, Rafał Frydrych, Jacek Mlynarski, Olena Vakuliuk, Daniel T. Gryko, Bartosz A. Grzybowski

“…Moreover, when supplemented by models to approximate kinetic rates, the algorithm can predict reaction yields and identify reactions that have potential for organocatalysis. …”
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Multi-exit Kolmogorov–Arnold networks: enhancing accuracy and parsimony by James Bagrow, Josh Bongard

“…Here we introduce multi-exit KANs, where each layer includes its own prediction branch, enabling the network to make accurate predictions at multiple depths simultaneously. …”
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Implementasi Algoritma Support Vector Machine (SVM) Untuk Klasifikasi Penyakit Stroke by Danis Rifa Nurqotimah, Ahsanun Naseh Khudori, Risqy Siwi Pradini

“…Classification is one of a few methods in predicting stroke symptoms with the aim of obtaining accurate prediction of disease. …”
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Neural network training to support decision making ON FOREX MARKET by V. A. Rybak, H. M. Sulaiman

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Exploration for the physical origin and impact of chemical short-range order in high-entropy alloys: Machine learning-assisted study by Panhua Shi, Zhen Xie, Jiaxuan Si, Jianqiao Yu, Xiaoyong Wu, Yaojun Li, Qiu Xu, Yuexia Wang

“…In this study, we introduced a set of interpretable ML workflows and determined the best algorithm (kernel ridge regression (KRR)) for predicting the atomic stress in HEAs, which can deepen the understanding of the formation mechanism of CSRO. …”
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Identification method of roof rock interface based on response characteristics of drilling parameters by LI Dianshang, LIU Cancan, WANG Chuanbing, REN Bo, REN Shuai, KANG Zhipeng

“…On-site tests yielded 0.04m of average error in predicting the position of the coal rock interface. …”
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Measurement Error Estimation Method of Field Service Electricity Energy Meters under the Condition of Big Data by DAI Yan-jie, DONG Xian-guang, LIU Ya-qi, LIANG Ya-jie, LIU Xiao, QI Jia, SUN Yong-quan

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