Estimating Daily Rice Crop Evapotranspiration in Limited Climatic Data and Utilizing the Soft Computing Algorithms MLP, RBF, GRNN, and GMDH by Pouya Aghelpour, Hadigheh Bahrami-Pichaghchi, Farzaneh Karimpour

“…For this model, both the Nash-Sutcliffe (NS) coefficient and R2 were greater than 0.98, and the Root Mean Square Error (RMSE) ranged between 0.214 and 0.234 mm per day in all stations. …”
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On the influence of cross-sectional deformations on the aerodynamic performance of wind turbine rotor blades by J. Gebauer, F. Prigge, D. Ahrens, L. Wein, C. Balzani

“…This paper provides an initial estimation of the extent to which cross-sectional deformations influence the aerodynamic loads on the rotor. The IEA 15 MW reference wind turbine model is used for this study. …”
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Smart Irrigation Manager: A Simple User-Friendly Software for Determining Irrigation Scheduling by Hassan M. Abd El Baki, Asad Sarwar Qureshi, Haruyuki Fujimaki

“…SIM fairly estimated the daily ET0 using the FAO-PM method with average root mean squared error (RMSE) of 0.05 mm d‒1, while the daily estimates using the Hargreaves and Blaney‒Criddle methods were overestimated with average RMSE of 0.45 mm d‒1 and 2.1 mm d‒1, respectively. …”
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Impact of Climate Change on the Thermoeconomic Performance of Binary-Cycle Geothermal Power Plants by Paolo Blecich, Igor Wolf, Tomislav Senčić, Igor Bonefačić

“…The predictive power of the CMIP6 climate models is evaluated using the root mean square error (<i>RMSE</i>) and the Kullback–Leibler (<i>KL</i>) criteria. …”
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A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm by Yong Fan, Guangdong Yang, Yong Pei, Xianze Cui, Bin Tian

“…This research provides a reference for accurate PPV prediction at complex sites.…”
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Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm. by Jiayuan Wang

“…It has better prediction performance than the combination model, with a coefficient of determination approaching 1.0, a fitting accuracy of 0.994, a mean square error of 0.1947, a root mean square error of 0.3847, and an average absolute percentage error of 15.23%. …”
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University proceedings. Volga region. Technical sciences by V.N. Ashanin, A.A. Korotkov

“…An experimental study was conducted and the values of the root mean square deviation (RMS) of the linearity of the ADC conversion function were obtained using an ideal integrating capacitor, as well as with the addition of an integrating capacitor equivalent circuit with a number of absorption coefficient values to the model. …”

Deep Learning-Based Vertical Decomposition of Ionospheric TEC into Layered Electron Density Profiles by Jialiang Zhang, Jianxiang Zhang, Zhou Chen, Jingsong Wang, Cunqun Fan, Yan Guo

“…Experimental validation against COSMIC-2 radio occultation observations in 2019 demonstrates the model’s capability to capture ionospheric vertical structures, with a prediction performance significantly outperforming the International Reference Ionosphere model IRI-2020: root mean square error (RMSE) decreased by 34.16%, and the coefficient of determination (R²) increased by 28.45%. …”
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Can gridded real‐time weather data match direct ground observations for irrigation decision‐support? by Samikshya Subedi, Ayoub Kechchour, Michael Kantar, Vasudha Sharma, Bryan C. Runck

“…We evaluate the data sources directly for goodness‐of‐fit for solar radiation, temperature (min and max), dew point, and wind speed, as well as downstream predictions of reference ET (ETref) and GDD. Our findings show that gridded data, despite its tendency to overestimate solar radiation, does not significantly impact the accuracy of ET (R2 = 0.92 for 2022 and 0.93 for 2023; root mean square error [RMSE] = 0.55 mm for 2023) or GDD predictions (R2 = 0.99 for 2022 and 0.98 for 2023; RMSE = 0.53°C [2022], RMSE = 0.70°C [2023]). …”
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Calibration of the Composition of Low-Alloy Steels by the Interval Partial Least Squares Using Low-Resolution Emission Spectra with Baseline Correction by M. V. Belkov, K. Y. Catsalap, M. A. Khodasevich, D. A. Korolko, A. V. Aseev

“…Based on the laser emission spectra of 65 reference samples of low-alloy steels registered in the wavelength range 172–507 nm with a spectral resolution of 0.5 nm and a step of 0.1 nm, the following calibration models were developed: for carbon concentration with a root mean square error 0.059 % in the range ≤ 0.8 %, for manganese – 0.02 % and 2.0 %, respectively, chromium – 0.009 % and 1.0 %, silicon – 0.021 % and 1.2 %, nickel – 0.04 % and 0.8 %, copper – 0.019 % and 0.5 %, vanadium and titanium – 0.005 % without range limitation. …”
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Wearable Multimodal Sensor Probe for Monitoring Core Body Temperature, Electrocardiogram, Heart Rate, and Sweat Rate by Yuki Hashimoto, Kota Noto, Soto Tada, Yoshifumi Nishida

“…Validation experiments were conducted with ten healthy adult men performing cycling exercises under controlled environmental conditions, with the accuracy of each measurement obtained from the prototype evaluated by comparison with reference values. The results showed root mean squared errors of 0.087&#x00B0;C for core body temperature and 131 g for total water loss, both surpassing the accuracy of previous studies. …”
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An eco-friendly chemometrics assisted UV spectrophotometric method for simultaneous determination of sofosbuvir, simeprevir and ledipasvir in pharmaceuticals by Adil Alshehri, Ali Alqahtani, Abdulrhman Alsayari, Ahmed A. Almrasy

“…Application to commercial pharmaceuticals yielded excellent recoveries (99.70–100.39%) with no statistically significant difference from reference high-performance liquid chromatography (HPLC) methods. …”
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Performance Evaluation of Satellite Precipitation Products During Extreme Events—The Case of the Medicane Daniel in Thessaly, Greece by Dimitrios Katsanos, Adrianos Retalis, John Kalogiros, Basil E. Psiloglou, Nikolaos Roukounakis, Marios Anagnostou

“…Indeed, most of the satellite precipitation products studied in this work showed a misplacement of the highest amounts of associated rainfall, a significant underestimation of the event, and large unbiased root mean square error in the areas of heavy precipitation. …”
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Automated generation of an urban synthetic elevation checkpoint network across the North Carolina coastline, USA by Alexander Seymour, Christine Kranenburg, Kara Doran

“…Consideration of a topographic model's vertical root mean squared error (RMSEz) and systematic directional bias is important for many of these applications, particularly landscape change detection and measurement. …”
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Modeling compaction effects on soil water retention across the full moisture range: Calibration and validation by Andre Peters, Zhengchao Tian, Joshua L. Heitman, Sascha C. Iden, Lennart Rolfes, Kai Germer, Marco Lorenz

“…All other parameters can either be fixed at the reference value or scaled based on straightforward physical reasoning. …”
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Deep Learning‐Based Prediction of Global Ionospheric TEC During Storm Periods: Mixed CNN‐BiLSTM Method by Xiaochen Ren, Biqiang Zhao, Zhipeng Ren, Yan Wang, Bo Xiong

“…The results indicate that using historical TEC in the solar‐geographical reference frame as input driving data achieves higher prediction accuracy compared to that in the geocentric coordinate system. …”
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A Rice Leaf Area Index Monitoring Method Based on the Fusion of Data from RGB Camera and Multi-Spectral Camera on an Inspection Robot by Yan Li, Xuerui Qi, Yucheng Cai, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaohu Zhang

“…This study provides a technical reference for automatically monitoring rice growth parameters in the field using inspection robots.…”
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Experimental Study on the Complex Contact Frictional Property of an Ultralong Distance Large-Section Concrete Pipe Jacking and Prediction of Pipe String Stuck by Ziyong He, Jiangong Chen

“…The methodology of this study can provide a reference for other studies concerning the jacking force of long-distance rock microshield tunnelling.…”
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Missing Data Interpolation of Alzheimer’s Disease Based on Column-by-Column Mixed Mode by Shi-di Miao, Si-qi Li, Xu-yang Zheng, Rui-tao Wang, Jing Li, Si-si Ding, Jun-feng Ma

“…In addition, in the processing of missing data, a combination of deletion method and interpolation method is adopted with reference to expert knowledge. Compared with the direct interpolation method, the data set obtained by this method is more accurate.…”
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Using the SEIQR model with epidemic amplifier effect to predict the final outbreak size of the COVID-19 in Dalian, Liaoning province, China. by Qingyu An, Jun Wu, Wen Hui Chen

“…The mean absolute relative error(MARE), root mean squared error(RMSE) and mean absolute error(MAE) were used to assess the predictive capacity of the model.…”
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