Praveen Kumar Tyagi

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In this paper, diagnosis of diabetes using soft computing is presented. This research work is based on the fuzzy if-then rules and tuning of the parameters by neural network. A variational method for determining, globally optimal learning parameters and learning rules for on-line gradient descent training has been proposed in the paper. Neurofuzzy system is(More)
Artificial intelligence is a set of real time computational methodologies to address complex real-world problems. In this paper, Neurofuzzy Inference System for analysis of pulmonary tuberculosis (TB)disease is discussed. For effective result, simulation is being done by using the realistic causes of pulmonary TB. The Neurofuzzy system is used for decision(More)
In this paper, we are using Neurofuzzy system for either prediagnosis or preidentification of leukemia. Mainly the technique of Backpropagation algorithm is used in order to complete the process of training and testing our data, that (data) has already been obtained by generating the Sugeno based model of all considered rules, based on different symptoms of(More)
In this paper, a structure of adaptive system is proposed with the help of Neurofuzzy System (NFS) for diagnosis of Malaria. Investigation of malaria using Neurofuzzy system has been used for decision making ability based on predefined rules and learning by the backpropagation algorithm. Mapping Network in backpropagation algorithm is applied to minimize(More)
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