Results 11 to 20 of about 1,354,279 (305)
Agriculture, 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
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Minimum Mean Squared Error interference alignment [PDF]
2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, 2009 David A. Schmidt +4 more
openalex +2 more sources
Correcting the Bias of the Root Mean Squared Error of Approximation Under Missing Data
Methodology, 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
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Mean Squared Error Analysis of Quantizers With Error Feedback [PDF]
IEEE Transactions on Signal Processing, 2016 Quantization is a fundamental process in digital signal processing. $\Delta \Sigma$ modulators are often utilized for quantization, which can be easily implemented with static uniform quantizers and error feedback filters.
S. Ohno +3 more
semanticscholar +1 more source
Frontiers 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
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Genomes to Fields 2022 Maize genotype by Environment Prediction Competition
BMC 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
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Developing Novel Robust Loss Functions-Based Classification Layers for DLLSTM Neural Networks
IEEE 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
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Mid-Term Residential Load Forecasting Based on Neighborhood Component Analysis Feature Selection [PDF]
هوش محاسباتی در مهندسی برق, 2022 Residential load forecasting plays an important role in management and planning in modern smart grids. In planning to keep demand and supply balanced, accurate residential load forecasting is needed.
Iman Bahadornejad +4 more
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Applied 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
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Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not
Geoscientific Model Development, 2022 . The root-mean-squared error (RMSE) and mean absolute error (MAE) are widely used metrics for evaluating models. Yet, there remains enduring confusion over their use, such that a standard practice is to present both, leaving it to the reader to decide ...
T. Hodson
semanticscholar +1 more source