Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line by Sahatsawat Wainiphithapong, Chana Phutthananon, Sompote Youwai, Pitthaya Jamsawang, Phattarawan Malaisree, Ochok Duangsano, Pornkasem Jongpradist

“…For simplification and practical field implementation, the same set of SOP values is applied across all 11 timesteps during the optimization process. Using the proposed optimization framework, the optimal results demonstrate improvements in Pavg, increasing by up to 109.8% (from 13.99 to 29.35 mm) and in S, reducing up to 79.6% (from 34.55 to 7.06 mm) when MOO is conducted as a time series using the simplified method. …”
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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…The GVSAO algorithm is a sophisticated optimization technique that fine-tunes the hyperparameters of CNNs. …”
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Advanced removal of butylparaben from aqueous solutions using magnetic molybdenum disulfide nanocomposite modified with chitosan/beta-cyclodextrin and parametric evaluation through... by Saeed Hosseinpour, Alieh Rezagholizade-shirvan, Mohammad Golaki, Amir Mohammadi, Amir Sheikhmohammadi, Zahra Atafar

“…The predictive stability of PR emerges through these different dataset applications. The L-BFGS algorithm established the optimal control factors as pH = 6.64 and initial concentration = 1.00 mg/L and contact time = 60 min and adsorbent dosage = 0.8 g/L which dramatically improved the removal efficiency due to the collaborative properties of the nanocomposite. …”
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Research on Offshore Vessel Trajectory Prediction Based on PSO-CNN-RGRU-Attention by Wei Liu, Yu Cao

“…This study utilizes real Automatic Identification System (AIS) data and applies the PSO algorithm to optimize the model and determine the optimal parameters, using a sliding window method for input and output prediction. …”
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PERFORMANCE PREDICTION OF ROADHEADERS USING SUPPORT VECTOR MACHINE (SVM), FIREFLY ALGORITHM (FA) AND BAT ALGORITHM (BA) by Arash Ebrahimabadi, Alireza Afradi

“…Additionally, this study employed Firefly Algorithm (FA), Bat Algorithm (BA) and Support Vector Machine (SVM), which were assessed using coefficient of determination (R²), root mean square error (RMSE), mean squared error (MSE) and mean absolute error (MAE).The obtained results for Firefly Algorithm (FA) are found to be as R2 = 0.9104, RMSE = 0.0658, MSE= 0.0043 and MAE= 0.0039, for Bat Algorithm (BA) are found to be as R2 = 0.9421, RMSE = 0.0528, MSE= 0.0027 and MAE= 0.0024, and for Support Vector Machine (SVM) are found to be as R2 = 0.8795, RMSE = 0.0762, MSE= 0.0058 and MAE= 0.0052, respectively. …”
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Improving Vehicle Dynamics: A Fractional-Order PI<i>^λ</i>D<i>^μ</i> Control Approach to Active Suspension Systems by Zongjun Yin, Chenyang Cui, Ru Wang, Rong Su, Xuegang Ma

“…A fractional-order PI<i>^λ</i>D<i>^μ</i> (FOPID) controller was proposed, and its structural parameters were optimized using a gray wolf optimization algorithm. …”
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Study on Tourism Development Using CRITIC Method for Tourist Satisfaction by Xi Yang, Noor Azman Ali, Huam Hon Tat

“…These weights informed the MLP model, which accurately predicted tourist satisfaction with a mean absolute error (MAE) of 0.12 and a root mean square error (RMSE) of 0.18. Using the GA, the study identified optimal strategy combinations that improved satisfaction scores by up to 15% compared to baseline strategies. …”
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Integrating Multilayer Perceptron and Support Vector Regression for Enhanced State of Health Estimation in Lithium-Ion Batteries by Sadiqa Jafari, Jisoo Kim, Wonil Choi, Yung-Cheol Byun

“…We utilized Support Vector Regression (SVR) and Multilayer Perceptron (MLP) models, which were fine-tuned using hyperparameter optimization. The models were assessed using evaluation metrics such as Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and R-squared <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

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Reinforcing long lead time drought forecasting with a novel hybrid deep learning model: a case study in Iran by Mahnoosh Moghaddasi, Mansour Moradi, Mahdi Mohammadi Ghaleni, Zaher Mundher Yaseen

“…Key parameters of the DFFNN, including the number of neurons and layers, learning rate, training function, and weight initialization, were optimized using the WSO algorithm. The model’s performance was validated against two established optimizers: Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions by Yuxiang Guo, Qiang Han, Tan Li, Huichu Fu, Meng Liang, Siwei Zhang

“…Additionally, the Whale Optimization Algorithm is adopted to efficiently optimize the hyperparameters of iTransformer for the framework, improving parameter adaptability and convergence efficiency. …”
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Neural network-based link prediction algorithm by Yonghao PAN, Hongtao YU, Shuxin LIU

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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Results demonstrate that the CNN-LSTM-BMO achieves superior performance with the lowest Root Mean Square Error (RMSE) of 0.5523 and highest R² value of 0.9435, showing statistically significant improvements over other optimization methods as confirmed by paired t-tests (P < 0.05). …”
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Application of HHO-CNN-LSTM-based CMAQ correction model in air quality forecasting in Shanghai by ZHENG Xinnan, LIN Kaiyan, WANG Zijing, SONG Yuanbo, SHI Yang, LU Hanyue, ZHANG Yalei, SHEN Zheng*

“…To address the propensity of the HHO algorithm to converge on local optima, leading to poor CO correction performance, this study proposed a method for the HHO algorithm with a Gaussian random walk strategy to improve the CO concentration correction performance.…”
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Evaluation of geological engineering factors for productivity of deep CBM well after fracturing based on grey correlation method by KONG Xiangwei,XIE Xin,WANG Cunwu,SHI Xian

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Delphi consensus statement for the management of delayed post-polypectomy bleeding by Enrique Rodríguez de Santiago, Sandra Pérez de la Iglesia, Diego de Frutos, José Carlos Marín-Gabriel, Carolina Mangas-SanJuan, Raúl Honrubia López, Hugo Uchima, Marta Aicart-Ramos, Miguel Ángel Rodríguez Gandía, Eduardo Valdivielso Cortázar, Felipe Ramos Zabala, Marco Antonio Álvarez, Marina Solano Sánchez, Jesús Manuel González Santiago, Eduardo Albéniz, Gonzalo Hijos-Mallada, Nerea Castro Quismondo, Miguel Fraile-López, David Martínez Ares, Javier Tejedor-Tejada, Luis Hernández, Joan B. Gornals, Sergi Quintana-Carbo, Juan Ocaña, João A. Cunha Neves, Juan Martínez Martínez, María López-Cerón Pinilla, Carlos Dolz Abadía, María Pellisé

“…These recommendations aim to improve patient outcomes and optimize healthcare resources while fostering a standardized approach to this common adverse event.…”
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Hardware implementation of RSA encryption algorithm based on pipeline by Yang Longfei, Lu Shi, Peng Kuang

“…To address the high cost of implementing long-bits RSA encryption algorithms in hardware, improvements have been made to the traditional radix-4 Montgomery algorithm. …”
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Dynamic Sharding and Monte Carlo for Post-Quantum Blockchain Resilience by Dahhak Hajar, Nadia Afifi, Imane Hilal

“…Previous research also found that post-quantum blockchains, despite their improved cryptographic algorithms, are still vulnerable to DDoS attacks, emphasizing the need for more resilient architectural solutions. …”
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Accounting of infiltration waters and the level of recharge of the root layer by groundwater when calculating the irrigation regime on drained lands by Mazhaysky Yuri, Pavlov Artyom

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THE ALGORITHM FOR THE TREATMENT OF PATIENTS WITH TREATMENT-RESISTANT HYPERTENSION AT THE OUTPATIENT STAGE by O. S. Kulbachuk, E. V. Sid, O. V. Soloviov, A. V. Piskun

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