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ANN models have very high accuracy for prediction and better forecasting performance than the other models. The proposed …
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discuss the a forementioned issues. Design/methodology/approach Going beyond the existing CCR prediction data, this study … intends to address the impact of supply chain data and network activity data on CCR prediction, by integrating machine … learning technology into the prediction to verify whether adding new data can improve the predictability. Findings The results …
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Missing value arises in almost all serious statistical analyses and creates numerous problems in processing data in databases. In real world applications, information may be missing due to instrumental errors, optional fields and non-response to some questions in surveys, data entry errors, etc....
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This article describes how agriculture is the main occupation of India, and how the economy depends on agricultural production. Most of the land in India is dedicated to agriculture and people depend on the production of agricultural products. Therefore, forecasting the accuracy of future events...
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Considering the complexity of vegetables price forecast, the prediction model of vegetables price was set up by … genetic algorithm and BP neural network are compared. The results show that the absolute error of prediction data is in the … scale of 10%; in the scope that the absolute error in the prediction data is in the scope of 20% and 15%. The accuracy of …
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Assume we have a dataset, Z say, from the joint distribution of random variables X and Y , and two further, independent datasets, X and Y, from the marginal distributions of X and Y , respectively. We wish to combine X, Y and Z, so as to construct an estimator of the joint density. This problem...
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