In this paper, we applied the support vector machine (SVM) to the spatial interpolation of the multi-year average annual precipitation in the Three Gorges Region basin. By combining it with the inverse distance weighting and ordinary kriging method, we constructed the SVM residual inverse distance weighting, as well as the SVM residual kriging precipitation interpolation model and compared them...

The support vector machine (SVM) is a popular classifier in machine learning, but it is not robust to outliers. In this paper, based on the Correntropy induced loss function, we propose the rescaled hinge loss function which is a monotonic, bounded and nonconvex loss that is robust to outliers. We further show that the hinge loss is a special case of the proposed rescaled hinge loss. Then, we d...

Confronted with the chaotic characteristics of landslide displacement and the deficiencies of traditional time series prediction model, the wavelet analysis -support vector machine model (WA-SVM) based on chaotic time series for landslide displacement prediction is proposed. On the basis of the analysis of chaotic characteristics, landslide displacement is decomposed in to components with diffe...

This paper proposes a Support Vector Machine (SVM) based combining scheme that incorporates ideolectal and acoustic characteristics for speaker recognition. Two statistical model paradigms, namely GMM for acoustic modeling and Bigrams for language modeling, provide multilevel speaker information that affords a better classification performance when SVM-based fusion is accomplished. This combini...

Artificial intelligence (AI) decision-making systems are already being extensively used to make decisions in situations where legal rules applied establish rights and obligations. In the United States, algorithmic employed determine of individuals disability benefits, evaluate performance employees, selecting who will be fired, assist judges granting or denying bail probation. this paper I expl...

The feasibility of using hyperspectral imaging with convolutional neural network (CNN) to identify rice seed varieties was studied. Hyperspectral images of 4 rice seed varieties at two different spectral ranges (380–1030 nm and 874–1734 nm) were acquired. The spectral data at the ranges of 441–948 nm (Spectral range 1) and 975–1646 nm (Spectral range 2) were extracted. K nearest neighbors (KNN)...

The slope stability analysis is routinely performed by engineers to estimate the stability of river training works, road embankments, embankment dams, excavations and retaining walls. This paper presents a new approach to build a model for the prediction of slope stability state. The support vector machine (SVM) is a new machine learning method based on statistical learning theory, which can so...