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This paper presents a novel approach to simulate a Knowledge Based System for diagnosis of Breast Cancer using Soft Computing tools like Artificial Neural Networks (ANNs) and Neuro Fuzzy Systems. The feed-forward neural network has been trained using three ANN algorithms, the Back propagation algorithm (BPA), the Radial Basis Function (RBF) Networks and the(More)
Breast cancer is the second leading cause of cancer deaths worldwide and occurrs in one out of eight women. In this paper we develop a system for diagnosis, prognosis and prediction of breast cancer using Artificial Neural Network (ANN) models. This will assist the doctors in diagnosis of the disease. We implement four models of neural networks namely Back(More)
A major problem in medical science is attaining the correct diagnosis of disease in precedence of its treatment. This paper presents the diagnosis of thyroid disorders using Artificial Neural Networks (ANNs). The feed-forward neural network has been trained using three ANN algorithms; the Back propagation algorithm (BPA), the Radial Basis Function (RBF)(More)
  • J. Jacqulin, Margret B. Lakshmipathi, +13 authors D. Selvathi
  • 2012
Thyroid gland secretes thyroid hormones to control the body's metabolic rate. The malfunction of thyroid hormone will leads to thyroid disorders. The under-activity and over-activity of thyroid hormone causes hypothyroidism and hyperthyroidism. This paper describes the diagnosis of thyroid disorders using decision tree attribute splitting rules. Since,(More)
The pace of development and automation urge the need of robots controlling much of the work which used to be done mainly by humans. The modern technology has emphasized on the need to move a robot in an environment which is dynamically changing. An example of such an application may be the use of robots in industry to carry tools and other materials from(More)
Robotic Path planning is one of the most studied problems in the field of robotics. The problem has been solved using numerous statistical, soft computing and other approaches. In this paper we solve the problem of robotic path planning using a combination of A* algorithm and Fuzzy Inference. The A* algorithm does the higher level planning by working on a(More)