Diabetic retinopathy (DR) is an eye disease caused by the complication of diabetes and we should detect it early for effective treatment. As diabetes progresses, the vision of a patient may start to deteriorate and lead to diabetic retinopathy. As a result, two groups were identified, namely non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). In this pape...

This study aimed to establish a machine learning (ML)-based rice blast predicting model decrease the appreciable losses based on short-term environment data. The average, highest and lowest air temperature, average relative humidity, soil temperature solar energy were selected for development. developed multilayer perceptron (MLP), support vector (SVM), Elman recurrent neural network (Elman RNN...

Different methods have been used to predict financial information manipulation that can be defined as the distortion of the information in the financial statements. The purpose of this paper is to predict financial information manipulation by using support vector machine (SVM) and probabilistic neural network (PNN). A number of financial ratios are used as explanatory variables. Test performanc...

Classification using a Polynomial Neural Network (PNN) can be considered as a multi-objective problem rather than as a single objective one. Measures like predictive accuracy and architectural complexity used for evaluating PNN based classification can be thought of as two different conflicting objectives. Using these two metrics as the objectives of classification problem, this paper uses a Pa...

We consider the probabilistic neural network (PNN) that is a mixture of Gaussian basis functions having different variances. Such a Gaussian heteroscedastic PNN is more economic, in terms of the number of kernel functions required, than the Gaussian mixture PNN of a common variance. The expectation-maximisation (EM) algorithm, although a powerful technique for constructing maximum likelihood (M...

Water-soluble cyclodextrins (CDs) bearing two nitrogen atoms as metal coordinating sites have been synthesized. An appropriate phosphane could be included within their cavity through the primary face to form self-assembled PNN supramolecular edifices. Once the PNN ligands were coordinated to platinum, the resulting complexes proved to be very effective as catalysts in a domino reaction, where a...

The purpose of the present study was the proposal of novel biomarkers in prostate cancer by analyzing mass spectrometry profiles. The latter were obtained from the National Cancer Institute Clinical Proteomics Database. The proposed method applied first a pre-processing pipeline of smoothing, automatic noise estimation, peak detection, and peak alignment, for improving the choice of information...

In this paper, we used 3D modeling and nonlinear methods (fractal, multifractal, and probabilistic neural networks (PNN)) for regional mineral potential mapping and quantitative assessment for porphyry and skarn-type Mo deposits and hydrothermal vein-type Pb–Zn–Ag deposits in the Luanchuan region, China. A 3D geological model was constructed from various geological maps, cross sections, borehol...

A new ensemble algorithm based on K-means clustering and probabilistic neural network called K-meansPNN for classifying the industrial system faults is presented. The proposed technique consists of a preprocessing unit based on K-means clustering and probabilistic neural network. Given a set of data points, firstly the K-means algorithm is used to obtain K-temporary clusters, and then PNN is us...

In this paper, Automation of a power system fault detection using multi resolution analysis (MRA) wavelet transform is proposed and the various coefficients obtained from wavelet transform are given as an input to the probabilistic neural network (PNN). This PNN will classify and find the nature of fault occurring. Later, the decisions obtained from the output of PNN can be used to tune the pow...