Artificial Intelligent Systems and Machine Learning

P. Pramila ¹, S. Purushothaman ²

Affiliations
1 Dept. of Electrical & Electronics Engg., Bangalore Institute of Technology, V.V Puram, K.R. Road, Bangalore-560004, IN
2 Department of Mechanical Engineering, PET Engineering College, Vallioor 627117, IN

Abstract

The paper presents implementation of neurofuzzy methods for estimating power quality. The electrical signal is collected and decomposed to obtain features. The estimated features were used as input parameters to Radial Basis Function (RBF) and Fuzzy Logic (FL) for training and testing to get the final weights. The resulted final weights were used for testing the proposed algorithms to estimate the power quality of the electrical signal.

Keywords

Radial Basis Function (RBF), Fuzzy Logic (FL), Power Quality Analysis.

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C. Berin Jones ¹, S. Suresh Kumar ², S. Purushothaman ³

Affiliations
1 Manonmaniam Sundaranar University 627012, IN
2 Vivekanandha College of Technology for Women, Tiruchencode-637205, IN
3 PET Engineering College, Vallioor-627117, IN

Abstract

This paper presents the implementation of back propagation algorithm (BPA), Fuzzy logic (FL) and graylevel co-occurrence matrix (GLCM) in identifying the exudates in diabetic retinopathy (DR) images. Human eyes are affected due to malnutrition and other present day exposure of eyes to different environments as continued work on the computer, watching television, watching small screen sized mobile phones. The eyes are strained in one form or other and damage to the nerves of the eyes occur which can be called DR, glaucoma and many other types. Representative features are obtained from the image. They are used for training the implemented algorithms. The performance of the three algorithms in identifying the exudates are presented.

Keywords

Gray Level Co-Occurrence Matrix (GLCM), Diabetic Retinopathy, Fundus Image, Artificial Neural Network (ANN), Fuzzy Logic (FL), Back Propagation Algorithm (BPA).

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P. Guhan ¹, S. Purushothaman ², R. Rajeswari ³

Affiliations
1 Department of MCA, VELS University, Chennai–600 117, IN
2 PET Engineering College, Vallioor, 627117, IN
3 Mother Teresa Women's University, Kodaikanal-624102, IN

Abstract

Fingerprint is a unique facility which is present in human anatomy. The ups and downs of the curvature present in the finger among human are different. The curvature present among male and female are also different. In general, the image of a finger either a thumb or index finger is scanned by a compact fingerprint scanner with high resolution. The fingerprint scanned w412ill go through preprocessing followed by wavelet decomposition. This paper implements wavelet decomposition for extracting features of fingerprint images. Subsequently, at the 5th level decomposition, statistical features are computed from the coefficients of approximation and detail. These features are used to train the radial basis function (RBF) neural network for identifying fingerprints. Sample finger prints are taken from database from the internet resource. The fingerprints are decomposed using daubauchi wavelet 1(db1) into 5 levels. The coefficients of approximation at the 5thlevel are used for calculating statistical features. These statistical features are used for training the RBF network.

Keywords

Fingerprint, Daubauchi Wavelet, Subband Wavelet Coefficients, Approximation and Details of 5 Level Decomposition, Radial Basis Function (Rbf).

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P. Sripriya ¹, S. Purushothaman ², R. Rajeswari ³

Affiliations
1 Department of MCA, VELS University, Pallavaram, Chennai-600117, IN
2 PET Engineering College, Vallioor, 627117, IN
3 Mother Teresa Women's University, Kodaikanal-624101, IN

Abstract

This paper presents the combined implementation of radial basis function(RBF) along with hidden Markov model (HMM) for human activity recognition. Surveillance cameras are installed in the crowded area in major metropolitan cities in various countries. Sophisticated algorithms are required to identify human walking style to monitor any unwanted behavior that would lead to suspicion. This paper presents the importance of RBF to identify the human GAIT. GAIT is one of the biometrics that can be measured at a distance and useful for security surveillance and biometric applications. The attraction of using GAIT as a biometric is that it is non-intrusive and typifies the motion characteristics specific to an individual. The proposed system attempt to recognize people by modeling each individual's GAIT using HMM. The HMM is a good choice for modeling a walk cycle because it can model sequential processes. This knowledge is used to generate a lower dimensional observation vector sequence which is then used to design a continuous density HMM for each individual

Keywords

GAIT, Human Walking Action, Radial Basis Function, Hidden Markov Model.

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R. I. Rajidap Neshtar ¹, S. Purushothaman ²

Affiliations
1 Department of Mechanical Engineering, Vinayaka Missions University, Salem, IN
2 Department of Mechanical Engineering, PET Engineering College, Tirunelveli District-627117, IN

Abstract

This paper presents estimation of stress and strain of a Rapid prototype product using artificial neural network (ANN). Radial basis function network is used to train the ANN topology. 3D model of blade is developed by using PROE. The model is analyzed using ANSYS to find the Von Mises stress and equivalent strain. The algorithm is trained using 15 values in the input layer of the ANN topology and two values in the output layer: stress and strain that are to be estimated during the testing stage of RBF algorithm.

Keywords

Radial Basis Function Network, Finite Element Method, Structural Analysis, and Blade.

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M. Suresh ¹, Maheswar Dutta ², S. Purushothaman ³

Affiliations
1 Mechanical Engineering, Sri Sai Ram Engineering College, Chennai-44, IN
2 M.N.R Engineering College, Hyderabad, IN
3 Mechanical Engineering, Udaya School of Engineering, IN

Abstract

This paper presents the implementation of functional back propagation algorithm (FUBPA) for estimating the power, torque, specific fuel consumption and presence of carbon monoxide, hydrocarbons in the emission of a direct injection diesel engine. Experimental readings were obtained using the biodiesel prepared from the waste cooking oil collected from the canteen of Sri Sairam Engineering College, India. This waste cooking oil was due to the preparation of varieties of food (vegetables fried and non vegetarian). To obtain the biodiesel, transesterification was done in chemical lab for more than a week, and the biodiesel was obtained. The biodiesel was mixed in proportions of 10%, 20%, 30%, 40%, 50% with remaining combinations of the diesel supplied by the Indian government. Variable compression ratio (VCR) diesel engine with single cylinder, 4 stroke diesel type was used.
The outputs of the engine as power, torque and specific fuel consumption were obtained from the computational facility attached to the engine. The data collected for different input conditions of the engine was further used to train FUBPA.
The trained FUBPA network was further used to predict the power, torque and SFC for different speed, biodiesel and diesel combinations and full load conditions. The estimation performance of the FUBPA network is discussed.

Keywords

Functional Back Propagation Algorithm, Waste Cooking Oil, Biodiesel.

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N. Austin ¹, P. Senthilkumar ², S. Purushothaman ³

Affiliations
1 Satyabama University, IN
2 Department of Mechanical Engineering, KSR College of Engineering, Tiruchengode, IN
3 Udaya School of Engineering, Kanyakumari District-629204, IN

Abstract

This paper presents implementation of Radial basis function (RBF) neural network to find out mixture of Hydrofluorocarbon (HFC) and Hydrocarbon (HC) for obtaining higher Coefficients of Performances (COPs). The thermodynamic properties of refrigerants are obtained using REFPROP 9 software that contains details of refrigerants. Different combinations of the refrigerants along with their COPs are obtained by the REFPROP 9. It consumes time in obtaining the correct combination of refrigerants as lot of menu options have to be chosen in the REFPROP 9. In order to make the process of finding out the correct mixed refrigerants with less manual intervention, RBF is trained and tested with the patterns of mixed refrigerants. The RBF mixed refrigerant analysis software has been developed by using MATLAB 10.

Keywords

Radial Basis Function, Artificial Neural Network, Mixed Refrigerant, Coefficient of Performance.

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P. Radha ¹, E. Ramaraj ², S. Purushothaman ³

Affiliations
1 Department of Computer Science and Engineering, Alagappa University, Karaikudi, IN
2 Computer Center, Alagappa University, Karaikudi, IN
3 Udaya School of Engineering, 629204, IN

Abstract

This paper discusses the preprocessing and classification of depression data using back propagation algorithm (BPA). In general, input vectors will not be orthogonal to each other. The proposed method of preprocessing the input vector makes possible BPA learn the input vectors. The classification performance of BPA have been shown for a minimum 80%.

Keywords

Depression Data, Back Propagation Algorithm, Polynomial Discriminant Vector (PDV).

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