Recently, a lot of attention has been devoted to advanced techniques of system modeling. PNN(polynomial neural network) is a GMDH-type algorithm (Group Method of Data Handling) which is one of the useful method for modeling nonlinear systems but PNN performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, w...

Object classification is important information for different transportation areas. This research developed a probabilistic neural network (PNN) classifier object using roadside Light Detection and Ranging (LiDAR). The objective was to classify the road user on urban into one of four classes: Pedestrian, bicycle, passenger car, truck. Five features calculated from point cloud generated LiDAR wer...

In this study, we introduce and investigate a class of neural architectures of Polynomial Neural Networks (PNNs), discuss a comprehensive design methodology and carry out a series of numeric experiments. PNN is a flexible neural architecture whose structure (topology) is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but becomes generated on t...

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...

The pandemic of coronavirus COVID-19 has created a great danger and concern for humanity. Many researchers have done different types work in this area to provide medical services. In paper, we proposed smart Covid-19 diagnosis system by using Feed Forward Backpropagation Neural Network (FFBNN) Probabilistic (PNN). Based on personal information from patients such as (age, gender, contact with si...

To enhance the precision of fault diagnosis for high-voltage direct-current (HVDC) systems by effectively extracting various types characteristics, a method based on long short-term memory network (LSTM) is proposed in this paper. The relies knowledge graph platform and developed using measured data from four an HVDC substation located southwest China. Firstly, constructed, then waveform prepro...

In this paper, recognition system for totally unconstrained handwritten characters for south Indian language of Kannada is proposed. The proposed feature extraction technique is based on Fourier Transform and well known Principal Component Analysis (PCA). The system trains the appropriate frequency band images followed by PCA feature extraction scheme. For subsequent classification technique, P...

The aim of this study was to investigate the usefiilness of gray scale morphological analysis in the assessment of atherosclerotic carotid plagues. Ultrasound images were recorded from 137 asymptomatic and 137 symptomatic plaques (Stroke, Transient Ischaemic Attack -TIA, Amaurosis Fugax-AF). The morphological pattern spectra of gray scale images were computed and two different classifiers named...

Zero insulators directly reduce the electrical performance of insulator strings, affecting safe and reliable operation transmission lines. The grounding current string contains characteristic information performance. Extracting can realize detection zero value insulator, which is great significance to ensure In this paper, composite used on ultra-high-voltage (UHV) lines studied analyze influen...

In this study, we propose a novel endoscopic manipulation system that is controlled by a surgeon’s eye movements. The optical axis direction of the endoscopic manipulator is altered intuitively based on the surgeon’s pupil movements. A graphical user interface was developed by dividing the monitor screen into several areas with shape boundaries, so that the movement direction of the endoscope c...