4 research outputs found

    Machine learning applied to the prediction of citrus production

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    An in-depth knowledge about variables affecting production is required in order to predict global production and take decisions in agriculture. Machine learning is a technique used in agricultural planning and precision agriculture. This work (i) studies the effectiveness of machine learning techniques for predicting orchards production; and (ii) variables affecting this production were also identified. Data from 964 orchards of lemon, mandarin, and orange in Corrientes, Argentina are analysed. Graphic and analytical descriptive statistics, correlation coefficients, principal component analysis and Biplot were performed. Production was predicted via M5-Prime, a model regression tree constructor which produces a classification based on piecewise linear functions. For all the species studied, the most informative variable was the trees’ age; in mandarin and orange orchards, age was followed by between and within row distances; irrigation also affected mandarin production. Also, the performance of M5-Prime in the prediction of production is adequate, as shown when measured with correlation coefficients (~0.8) and relative mean absolute error (~0.1). These results show that M5-Prime is an appropriate method to classify citrus orchards according to production and, in addition, it allows for identifying the most informative variables affecting production by tree

    Dam Safety. Overtopping and Geostructural Risks

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    This reprintshows recent advances in dam safety related to overtopping and the prevention, detection, and risk assessment of geostructural risks. Related to overtopping, the issues treated are: the throughflow and failure process of rockfill dams; the protection of embankment dams against overtopping by means of a rockfill toe or wedge-shaped blocks; and the protection of concrete dams with highly convergent chutes. In the area of geostructural threats, the detection of anomalies in dam behavior from monitoring data using a combination of machine learning techniques, the numerical modeling of seismic behavior of concrete dams, and the determination of the impact area downstream of ski-jump spillways are also studied and discussed. In relation to risk assessment, three chapters deal with the development of fragility curves for dikes and dams in relation to various failure mechanisms
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