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Grid Search for Lowest Root Mean Squared Error in Predicting Optimal Sensor Location in Protected Cultivation Systems [PDF]

open access: yesFrontiers in Plant Science, 2022
Irregular changes in the internal climates of protected cultivation systems can prevent attainment of optimal yield when the environmental conditions are not adequately monitored and controlled.
Daniel Dooyum Uyeh   +12 more
doaj   +2 more sources

Mean Squared Error Representative Points of Pareto Distributions and Their Estimation [PDF]

open access: yesEntropy
Pareto distributions are widely applied in various fields, such as economics, finance, and environmental studies. The modeling of real-world data has created a demand for the discretization of Pareto distributions.
Xinyang Li, Xiaoling Peng
doaj   +2 more sources

Mean Squared Error, Deconstructed [PDF]

open access: yesJournal of Advances in Modeling Earth Systems, 2021
AbstractAs science becomes increasingly cross‐disciplinary and scientific models become increasingly cross‐coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model
Timothy O Hodson   +2 more
exaly   +2 more sources

Optimizing LSTM Models for EUR/USD Prediction in the context of reducing energy consumption: An Analysis of Mean Squared Error, Mean Absolute Error and R-Squared [PDF]

open access: yesE3S Web of Conferences, 2023
The purpose of this study was to develop and evaluate a Long Short-Term Memory (LSTM) model for Forex prediction. The data used was reprocessed and the LSTM model was developed and trained using a supervised learning approach with popular deep learning ...
Echrigui Rania, Hamiche Mhamed
doaj   +1 more source

Correcting the Bias of the Root Mean Squared Error of Approximation Under Missing Data

open access: yesMethodology, 2021
Missing data are ubiquitous in psychological research. They may come about as an unwanted result of coding or computer error, participants' non-response or absence, or missing values may be intentional, as in planned missing designs.
Cailey E. Fitzgerald   +4 more
doaj   +1 more source

Towards Resilient Agriculture to Hostile Climate Change in the Sahel Region: A Case Study of Machine Learning-Based Weather Prediction in Senegal

open access: yesAgriculture, 2022
To ensure continued food security and economic development in Africa, it is very important to address and adapt to climate change. Excessive dependence on rainfed agricultural production makes Africa more vulnerable to climate change effects.
Chimango Nyasulu   +4 more
doaj   +1 more source

Agent-Based Modeling of Rumor Propagation Using Expected Integrated Mean Squared Error Optimal Design

open access: yesApplied System Innovation, 2020
In the “Age of the Internet”, fake news and rumor-mongering have emerged as some of the most critical factors that affect our online social lives. For example, in the workplace, rumor spreading runs rampant during times when employees may be plagued with
Shih-Hsien Tseng, Tien Son Nguyen
doaj   +1 more source

Overview and evaluation of various frequentist test statistics using constrained statistical inference in the context of linear regression

open access: yesFrontiers in Psychology, 2022
Within the framework of constrained statistical inference, we can test informative hypotheses, in which, for example, regression coefficients are constrained to have a certain direction or be in a specific order. A large amount of frequentist informative
Caroline Keck, Axel Mayer, Yves Rosseel
doaj   +1 more source

Developing Novel Robust Loss Functions-Based Classification Layers for DLLSTM Neural Networks

open access: yesIEEE Access, 2023
In this paper, we suggest improving the performance of developed activation function-based Deep Learning Long Short-Term Memory (DLLSTM) structures by employing robust loss functions like Mean Absolute Error $(MAE)$ and Sum Squared Error $(SSE)$ to ...
Mohamad Abou Houran   +5 more
doaj   +1 more source

Genomes to Fields 2022 Maize genotype by Environment Prediction Competition

open access: yesBMC Research Notes, 2023
Objectives The Genomes to Fields (G2F) 2022 Maize Genotype by Environment (GxE) Prediction Competition aimed to develop models for predicting grain yield for the 2022 Maize GxE project field trials, leveraging the datasets previously generated by this ...
Dayane Cristina Lima   +33 more
doaj   +1 more source

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