A novel multiscale feature enhancement network using learnable density map for red clustered pepper yield estimation by Chenming Cheng, Chenming Cheng, Jin Lei, Jin Lei, Zicui Zhu, Lijian Lu, Lijian Lu, Zhi Wang, Zhi Wang, Jiali Tao, Jiali Tao, Xinyan Qin, Xinyan Qin

“…Compared to other feature extraction networks, MFEN had the lowest mean absolute error (MAE) of 5.42, root mean square error (RMSE) of 10.37 and symmetric mean absolute percentage error (SMAPE) of 11.64%. …”
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Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

“…The proposed FLA-based PI controller achieved a reduction in maximum overshoot by 28.3 %, a decrease in settling time by 23.4 %, and an improvement in steady-state error by 15.7 % compared to the next best-performing optimization method. …”
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Models for sustainable management of livestock waste based on neural network architectures by Anatoliy Tryhuba, Krzysztof Mudryk, Inna Tryhuba, Marian Kotsylovskyi, Dmytro Sorokin, Olena Bezaltychna, Pawel Pysz, Taras Hutsol

“…The optimized MLP model demonstrated high predictive performance, achieving a mean squared error (MSE) of 0.0005 and a mean absolute percentage error (MAPE) of 6.51%, compared to 8.01% for the baseline model. …”
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A Novel Evolutionary Deep Learning Approach for PM_2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran by Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh

“…This paper employs a binary OA method for sensitivity analysis, optimizing feature selection by minimizing prediction error while retaining critical predictors through a penalty-based objective function. …”
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Data driven healthcare insurance system using machine learning and blockchain technologies by Irum Matloob, Shoab Khan, Bushra Bashir, Rukaiya Rukaiya, Javed Ali Khan, Hessa Alfraihi

“…The system provides recommendations with a root mean square error (RMSE) value of 0.478 and a mean absolute error (MAE) value of 0.0422. …”
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Evaluation of Four Semi‐Mechanistic Models for Predicting Glycemic Control With a Glucagon Receptor Antagonist in People With Type 2 Diabetes by Austin Yue Feng Tan, Karen Schneck, Parag Garhyan, Eric Chun Yong Chan, Lai San Tham

“…Metrics for predictive performance included: (a) mean change from baseline HbA1c (ΔHbA1c) at Week 24 between observed and simulated values; (b) mean prediction error (MPE) for bias; and (c) root mean squared error (RMSE) for precision. …”
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Prediction of Rut Depth in Soil Caused by Wheels Using Artificial Neural Networks by N. Farhadi, A. Mardani, A. Hosainpour, B. Golanbari

“…Specifically, the root mean square error (RMSE) for the optimal MLP model, which utilized a learning rate of 0.001 and a momentum of 0.67, was 0.10. …”
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MNPM: research on metabolic neural network prediction model for predicting carbon emission accuracy by Entao Luo, Li Shi, Jiyan Liu, Zheng Wu, Guoyun Duan, Lingxuan Zeng, Tangsen Huang

“…Accurately forecasting carbon emission trends is crucial for developing effective reduction strategies and ensuring sustainable green economic development. …”
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Application of quasi-oppositional driving training-based optimization for a feasible optimal power flow solution of renewable power systems with a unified power flow controller by Tushnik Sarkar, Chandan Paul, Susanta Dutta, Provas Kumar Roy, Ghanshyam G. Tejani, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…Obtaining minimum total cost comes under the single-objective function. Simultaneous reduction in the overall cost and emission, concurrent reduction in overall cost and voltage deviation (VD), and simultaneous reduction in overall cost and voltage stability index come under multi-objective cases. …”
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Revisiting the Chemical Composition of WD 1145+017: Impact of Circumstellar Disk Contamination on Photospheric Abundances by Érika Le Bourdais, Patrick Dufour, Siyi Xu

“…Our study underscores the importance of accounting for circumstellar absorption, as neglecting them leads to significant abundance errors. Additionally, the analysis of the disk’s opacity highlighted an ultraviolet flux reduction due to a pseudo-continuum due to an optically thick component. …”
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An Influence of Directional Microphones on the Speech Intelligibility and Spatial Perception by Cochlear Implant Users by Monika KORDUS, Richard S. TYLER, Jan ŻERA, Jacob J. OLESON

“…However localization in noise was less accurate as shown by a large number of considerable errors in localization in the confusion matrices. …”
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Integrating Sentinel-1 SAR and Machine Learning Models for Optimal Soil Moisture Sensor Placement at Catchment Scale by Yi Xie, Guotao Cui, Kaifeng Zheng, Guoping Tang

“…Results show that a network of nine optimally placed sensors minimized prediction errors (RMSE: 7.20%), outperforming both sparser and denser configurations. …”
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Enhancing Multi-Flight Unmanned-Aerial-Vehicle-Based Detection of Wheat Canopy Chlorophyll Content Using Relative Radiometric Correction by Jiale Jiang, Qianyi Zhang, Shuai Gao

“…The predictive accuracy of CCC models improved after the relative radiometric correction, with validation errors decreasing by 17.1–45.6% across different growth stages and with full-season integration yielding a 44.3% reduction. …”
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Exploring the Effect of a Wavy Sea Surface on NLOS-UOWC Systems: A Novel Deterministic Approach by Paulo Samaniego-Rojas, Rubén Boluda-Ruiz, José María Garrido-Balsells, Beatriz Castillo-Vázquez, Antonio Puerta-Notario, Antonio García-Zambrana

“…These findings enhance the preliminary considerations in NLOS link design, particularly in scenarios with autonomous underwater vehicles in constant motion, aiding in the reduction of pointing errors.…”
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Evaluation of Prediction Performances of Deep Learning Models for the Aerodynamic Characteristics of Flettner Rotors by Seo Janghoon, Park Jung Yoon, Ma Juhwan, Kim Young Bu, Park Dong-Woo

“…The aerodynamic force coefficients and flow fields are predicted by established deep learning models and show small absolute errors compared to those from the CFD analysis. Moreover, predicted flow fields reflect the flow characteristics according to the difference of spin ratio and arrangement of Flettner rotors. …”
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Parenteral administration medicines: recommendations of preparation, administration and stability by M. Gaspar Carreño, F. Torrico Martín, L. Novajarque Sala, M. Batista Cruz, P. Ribeiro Gonçalves, B. Porta Oltra, J. C. Sánchez Santos

“…The information provided will contribute to a reduction of errors associated with the preparation and administration of MAP.…”
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Model Predictive Control-Based Energy Management System for Cooperative Optimization of Grid-Connected Microgrids by Sungmin Lim, Jaekyu Lee, Sangyub Lee

“…Second, its robustness against prediction errors was tested by comparing scenarios with and without disturbance prediction. …”
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Towards developing an operational Indian ocean dipole warning system for Southeast Asia by Shipra Jain, Thea Turkington, Wee Leng Tan, Chen Schwartz, Adam A. Scaife, Theodore G. Shepherd

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Improved Synthesis of Global Irradiance with One-Minute Resolution for PV System Simulations by Martin Hofmann, Stefan Riechelmann, Cristian Crisosto, Riyad Mubarak, Gunther Seckmeyer

“…A comparison based on measurements performed in Lindenberg, Germany, and Carpentras, France, shows a reduction of the frequency distribution root mean square errors of more than 60% compared to the two existing synthesizing algorithms.…”
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Research on the Dynamic Modeling of Rigid–Flexible Composite Spacecraft Under Fixed Constraints Based on the ANCF by Jiaqi Wu, Guohua Kang, Junfeng Wu, Chuanxiao Xu, Jiayi Zhou, Xinyong Tao, Yinmiao Hua

“…The proposed model exhibits displacement errors less than 1 mm, highlighting its efficiency and accuracy.…”
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