Research Publications
Sep 1, 2013 publication descriptionInternational Journal of Scientific and Research Publications, Volume 3, Issue 9, September 2013
Neural network is the emerging field in the era of globalization which is fully based on the concept of softcomputing technique and bioinformatics. In the competitive market of new development process, Bioinformatics play the vital role to give the process of integration aspect as multidisciplinary subject like- biological Science, medicine science, computer science, engineering, chemical science,physical science as well as mathematical science who gives theexperiences of artificial activities of human behaviour in theform of software. Now a days neural Network and itsmultidimensional approach give the idea for solvingbioinformatics problems to handle imprecision, uncertainty inlarge and complex search spaces. This paper gives the emphasison multidimensional approaches of neural network with softcomputing paradigm using C# in bioinformatics with integrativeresearch methodology. The overall process of multidimensionalapproaches of bioinformatics neurons can also be understoodwith the help of flow chart and diagram is the major concerned.
Dec 22, 2013 publication description http://www.irjmst.com
The work is carried on the application of differential equation (DE) and its computational technique of genetic algorithm and neural (GANN) in C#, which is frequently used in globalized world by human wings. Diagrammatical and flow chart presentation is the major concerned for an easy undertaking of these two concepts with an indication of its present and future application is the new initiative taken in this paper along with computational approaches in C#. Little observation has been also pointed during working, functioning and development process of the above algorithm in C# under given boundary value condition of DE for genetic and neural. Operations of fitness function and Genetic operations were completed for behavioural transmission of chromosome. Overall working process of model is based on Initialization and Termination control of chromosome with its intermediates. Discussion is also extended with the presentation of similar application of neural & genetic concept used in various multidisciplinary fields. The computational of the DE model is verifies for a particular function (Mg(x) = exp(x)+sin(x)) which corresponds to the chromosome g for different quantities and penalty of fitness. Rule of thumb has been explained for better understanding of the Decision criteria on when to use Genetic Algorithms versus when to use Neural Networks to solve a problem is also presented Index Term: Boundary value Differential equation, Genetic & Neural Algorithm, Transmission of chromosome, Fitness function & Genetic operations and C# computation. Ref