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A new fault diagnosis system is proposed to recognize the faults of gear box in this paper by using the NMF-based characteristics extracting method and the neural networks technique. The results show that this method is effective for the fault diagnosis of gear box.
Data mining technique is an effective tool used to obtain desired knowledge from massive data. Neural network is a new method in the application of data mining. Although it may have shortcomings of complex structure, long training time and uneasily understandable representation of results, neural network has high accuracy which is superior to other methods and this makes it more available in data...
It is deficiency to use accuracy as a measurement to evaluate model classifying ability. This paper proposes a measurement method which uses the area under the ROC curve, or AUC value, to evaluate the performance of the model. Furthermore, applying cross validation and grid-search methods, through designed algorithms, to build an optimization of support vector machines medical prediction model. The...
This paper provides a method of discriminate analysis based on artificial neural network (ANN). 2-Class and multi-class discriminant analysis are separately discuss using Back Propagation network. The results of our study indicate that discriminate analysis based on ANN could classify the observation more accurately than the traditional methods.
This paper deals with the advanced and developed methodology know for cancer multi classification using an Extreme Learning Machine (ELM) for microarray gene expression cancer diagnosis, this used for directing multicategory classification problems in the cancer diagnosis area. ELM avoids problems like local minima; improper learning rate and over fitting commonly faced by iterative learning methods...
In this work, we proposed a novel authentication system based on facial features. The proposed method is based on PCA and LDA for feature extraction, these extracted features are combined using wavelet fusion. In this work we use neural networks to classify extracted features of faces. The proposed method consists of six steps: i) Extraction of images from the database, ii) Preprocessing, iii) Feature...
Accurate land use/cover (LUC) classification data derived from remotely sensed data are very important for land use planning and environment sustainable development. Traditionally, statistical classifiers are often used to generate these data, but these classifiers rely on assumptions that may limit their utilities for many datasets. Conversely, artificial neural network (ANN) and decision tree (DT)...
A tool for discovery of gait anomalies of elderly from motion sensor data is proposed. The gait of the user is captured with the motion capture system, which consists of tags attached to the body and sensors situated in the apartment. Position of the tags is acquired by the sensors and the resulting time series of position coordinates are analyzed with dynamic time warping and machine learning algorithms...
The Covering algorithm is proposed by Professor ZhangLing and ZhangBo in the 20th century, which simulates the structure of human learning, building a Constructive Neural Network Learning Model. Covering algorithm has been widely used to solve massive data classification problem, because its performance. The covering classification algorithm has fast learning, high recognition rate, massive data processing...
Supplier performance evaluation is a key issue of supply chain and is complicated since a variety of attributes must be considered. In this article, an integrated DEA-NN model is proposed. By taking advantages from both data envelopment analysis (DEA) and neural networks (NN), an application of the integrated DEA-NN method is given. The results indicate that the method is effective and applicable.
Medical data mining is so challenging. In this paper, we propose a new data mining algorithm called GAJA2, which is a derivation of GAJA [1]. We apply GAJA2 to mine Acute Inflammations data set, a medical data set got from UCI machine learning repository 2009[2]. This data set is about symptoms and diagnosis of two diseases of urinary system which are inflammation of urinary bladder and Nephritis...
This paper explores Bhattacharyya Distance principle and introduces it to recognize stego algorithms in use. First of all, we select the most important features by the means of applying Bhattacharyya distance. Then, BP neural network is used to classify cover and stego images. Extensive experimental works show that the proposed schemes have satisfactory performance on Jpeg steganography like F5, Outguess,...
Recent advances in neuroimaging demonstrate the potential use of functional near infrared spectroscopy (fNIRS) in the field of brain machine interface. An fNIRS uses light in the near infrared range to measure brain surface hemoglobin concentrations to determine a neural activity. The current study presents our empirical results in realizing fNIRS - BCI system. We analyze the hemodynamic responses...
In the last decade significant progress in computer vision based control of unmanned ground vehicles (UGV) has been achieved. However, until now textural information has been somewhat less effective than color or laser range information. In this paper we propose a computer vision based cross country segmentation system that is capable of distinguishing cross-country road, grass and trees during day-time...
Intelligent Space (IS), a kind of intelligent home, is one of the popular of the applying RT into our daily life. In intelligent space environment, human behavior is one of the meaningful information for interpretation of our intention and needs. In this paper, we proposed the human posture recognition approach which focuses on a top-view vision. A top-view vision enables our system to observe the...
At the dawn of the 3rd millennium, Human Handwriting Recognition is emerging from its infancy and set to become a mature technique. We shall probably see in the near future a number of mixed systems able to read both online and off-line handwriting. In this study we propose a simple yet robust structural solution for performing character recognition in Gujrati, the official language of Gujarat. Pursued...
This paper presents a new neural network architecture kernel principal component neural network (KPCNN) trained by threshold accepting based training algorithm with different kernels like polynomial, sigmoid and Gaussian and its application to bankruptcy prediction in banks. KPCNN is a non linear version of the PCNN proposed elsewhere. In this architecture, dimensionality reduction is taken care of...
Medical Diagnosis is the utmost need of an hour. Gestational Diabetics in women represents the second leading cause of yielding children born with birth defects. The ultrasound images are usually low in resolution making diagnosis difficult. Specialized tools are required to assist the medical experts to categorize and diagnose diseases to accuracy. If the anomalies in the ultrasound images are detected...
India is a multi-lingual multi-script country, where eighteen official scripts are accepted and there are over hundred regional languages. In this paper we propose a zone-based hybrid feature extraction algorithm scheme towards the recognition of off-line handwritten numerals of two popular south-Indian scripts. The character centroid is computed and the character/numeral image (50 ?? 50) is further...
Artificial neural networks are significantly used in the field of ophthalmology for accurate disease identification which further aids in treatment planning. In this paper, an automated system based on Self-Organizing neural network (Kohonen network) is proposed for eye disease classification. Abnormal retinal images from four different classes namely non-proliferative diabetic retinopathy (NPDR),...
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