Architecture for an efficient integration of wireless sensor networks to the Internet through Internet of Things gateways by Patrick Olivier Kamgueu, Emmanuel Nataf, Thomas Djotio

“…Gateway selection procedure at this layer was implemented using CPLEX linear solver, and the gateway was integrated on Raspberry Pi cheaper hardware which serves as the routing protocol for low-power and lossy network root for the wireless sensor network configuration. …”
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Dynamic Route Choice Prediction Model Based on Connected Vehicle Guidance Characteristics by Jiangfeng Wang, Jiarun Lv, Chao Wang, Zhiqi Zhang

“…A simulation scenario is established by programming different agents for controlling the flow of vehicles and for information acquisition and transmission. …”
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Modeling the number of tourist arrivals in the United States employing deep learning networks by Cagatay Tuncsiper

“…In order to quantify the performance of the developed model, the performance metrics namely coefficient of determination, mean absolute error, mean absolute percentage error and the root mean square error are computed. The coefficient of determination of the developed model is found to be over 0.95 indicating the high accuracy of the model. …”
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Joint DOA-delay estimation approach based on atomic norm by XU Ming, TANG Qian

“…The experimental results show that the root mean square error (RMSE) of the proposed approach is as low as 0.2° when the signal-to-noise ratio (SNR) is 20 dB, and there is still a 77.98% estimation success probability when the DOA interval is as low as 3°. …”
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Low pressure PEM electrolyzer system modeling with heat loss representation by Asmaa A. Ghany, Mohamed Mahmoud Samy

“…MATLAB programming is used to develop the model and evaluate the accuracy of the proposed identification method.…”
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Prediction of particulate matter PM2.5 level in the air of Islamabad, Pakistan by using machine learning and deep learning approaches by Muhammad Waqas, Shahid Noor Jan, Basir Ullah, Afed Ullah Khan, Ateeq Ur Rauf, Bakht Niaz Khan

“…Each model's performance was assessed by using statistical indicators including coefficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Relative Root Mean Square Error (RRMSE). …”
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Re-imagining Broadcasting in the Public Interest. SABC TV Broadcasting in a Commercialised Competitive Media System by Momelezi Kula, Maud Blose

“…The notion of the rainbow nation is rooted in diverse cultures and the different racial makeup of South Africa. …”
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Advocacy for DOHaD research optimizing child kidney health by You-Lin Tain

“…However, the intricate kidney programming mechanisms underlying these risks remain complex and are incompletely understood, but they are rooted in structural and functional alterations within the kidneys. …”
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RESEARCH ON INCREASING WORK EFFICIENCY IN THE MECHANISATION OF GERMINATION BED PREPARATION WORKS by Anișoara DUMA COPCEA, Nicoleta MATEOC-SÎRB, Casiana MIHUȚ, Lucian NIȚĂ, Simona NIȚĂ, Teodor MATEOC, Adalbert OKROS, Natalia MOCANU

“…The main methods utilized to optimize the use of agricultural aggregates are mathematical programming, direct calculus solutions, and operating nomograms. …”
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A deep learning approach: Physics-informed neural networks for solving the 2D nonlinear Sine–Gordon equation by Alemayehu Tamirie Deresse, Tamirat Temesgen Dufera

“…We evaluated the accuracy of the model by comparing it to other standard numerical methods in the literature through root mean square error (RMSE), L∞, and L2 relative errors. …”
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On The Pros and Cons of Using Excel for Regression Analysis by Sencer Buzrul

“…For linear models (linear in parameters) Excel Add-In Data Analysis-Regression tool creates a summary output, and parameter estimates, parameter uncertainties, adjusted R2 (R2adj) and root mean square error (RMSE) values can be found even for the models that do not exist in Excel. …”
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System Optimization of Talent Life Cycle Management Platform Based on Decision Tree Model by Jiaonan Han

“…The judgment process is from the root node to the leaf node. Each branch of the tree takes the form of selecting the best split attribute. …”
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Predictive Equations for Estimation of the Slump of Concrete Using GEP and MARS Methods by Ismail Husein, Ramaswamy Sivaraman, Sarwar Hasan Mohmmad, Forqan Ali Hussein Al-Khafaji, Sokaina Issa Kadhim, Yousof Rezakhani

“…This paper developed two robust data-driven models, namely gene expression programming (GEP) and multivariate adaptive regression splines (MARS), for the estimation of the slump of concrete (SL). …”
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Prediction of soil permeability coefficient using the GEP approach by Mina Torabi, Hamed Sarkardeh, S.Mohammad Mirhosseini

“…Therefore, this study used the Gene Expression Programming (GEP) model as a powerful data-driven technique for the estimation of k. …”
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Advanced computational approaches for predicting sunflower yield: Insights from ANN, ANFIS, and GEP in normal and salinity stress environments. by Sanaz Khalifani, Reza Darvishzadeh, Majid Montaseri, Sarvin Zaman Zad Ghavidel, Hamid Hatami Maleki, Mojtaba Kordrostami

“…Therefore, the GEP model provides a promising tool for predicting sunflower grain yield, potentially aiding in yield improvement programs under varying environmental conditions.…”
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Data-driven modeling of the aggregator-based price-maker virtual power plant (VPP) in the day-ahead wholesale electricity markets; evidence from the Japan Electric power Exchange (... by Mohamed Saad Suliman, Hooman Farzaneh

“…The results are validated against the JEPX market, showing an annual root mean squared error and mean absolute error of 5.14 and 3.55 ¥/kWh, respectively. …”
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Protein docking by the underestimation of free energy funnels in the space of encounter complexes. by Yang Shen, Ioannis Ch Paschalidis, Pirooz Vakili, Sandor Vajda

“…The method, called semi-definite programming-based underestimation (SDU), employs a general quadratic function to underestimate a set of local energy minima and uses the resulting underestimator to bias further sampling. …”
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Overvoltage Simulation Analysis and Suppression of Breaking in a 35 kV Shunt Reactor by Jing Chen, Xiaoyue Chen, Siying Feng, Xinmeng Liu, Qin Liu

“…It is concluded that the equivalent chopping current of the other two phases caused by the continuous reignition of the first open phase is the root cause of the high-amplitude interphase overvoltage. …”
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Non-intrusive Load Identification Method Based on the Online Self-organizing Incremental Neural Network—Non-intrusive load identification method based on the online self-organizing... by Zhengwei HU, Zhihong WANG, Ruixin CHANG, Zhiyuan XIE, Wangbin CAO

“…In the process of load feature extraction, a 12-dimensional feature extraction scheme was proposed, which includes the odd harmonics, the mean value, the variance value, the third-order moment, the fourth-order moment, the root mean square current, the peak value of power spectrum, and the trough value of power spectrum. …”
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Water temperature prediction in a subtropical subalpine lake using soft computing techniques by Saeed Samadianfard, Honeyeh Kazemi, Ozgur Kisi, Wen-Cheng Liu

“…In this paper, the performance of soft computing techniques including gene expression programming (GEP), which is a variant of genetic programming (GP), adaptive neuro fuzzy inference system (ANFIS) and artificial neural networks (ANNs) to predict hourly water temperature at a buoy station in the Yuan-Yang Lake (YYL) in north-central Taiwan at various measured depths was evaluated. …”
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