Results 11 to 20 of about 932,989 (354)
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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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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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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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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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
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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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New robust iterative minimum mean squared error-based interference alignment algorithm
The Journal of Engineering, 2014 Interference alignment (IA) is a promising technique for multiple input multiple output interference channels based systems, achieving the theoretical bound on degrees of freedom.
Sara Teodoro +4 more
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Decomposition of the mean absolute error (MAE) into systematic and unsystematic components
PLoS ONE, 2023 When evaluating the performance of quantitative models, dimensioned errors often are characterized by sums-of-squares measures such as the mean squared error (MSE) or its square root, the root mean squared error (RMSE).
S. Robeson, C. Willmott
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