Soft Computing Approaches

9th International Conference on Soft Computing, Artificial Intelligence and Applications (SAI 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Soft Computing. The conference looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.  Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to

3rd International Conference on Machine Learning and Soft Computing (MLSC 2022) will
provide an excellent international forum for sharing knowledge and results in theory, methodology
and applications Machine learning and Soft Computing. The aim of the conference is to provide a
platform to the researchers and practitioners from both academia as well as industry to meet and
share cutting-edge development in the field.

Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in
the areas of Machine learning, Soft Computing and applications.

Scope International Journal of Artificial Intelligence and Soft Computing (IJAISC) is an open access peer-reviewed journal that provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Soft Computing. The Journal looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Soft Computing, Artificial Intelligence and Applications.

This research paper presents the effect of % replacement of cement by fly ash (Class-F) on the compressive strength of fly ash cement concrete (FACC). This research work describes the feasibility of using the fly ash (Class-F) in concrete production as partial replacement of cement by weight. The cement has been replaced by fly ash accordingly in the range of 0% (without fly ash), 10%, 20%, 30% and 40% by weight of cement for the M-40 grade concrete mix. By using SPSS, standing for " Statistical Package for the Social Sciences " , is a powerful, user-friendly software package for the manipulation and statistical analysis of data. This software is useful for researchers in psychology, sociology, psychiatry, and other behavioral sciences, containing as it does an extensive range of both univariate and multivariate procedures much used in these disciplines. We have used it here to know the behavior of the concrete when cement is partially replaced by fly ash. By using SPSS software and excel sheet data the statistical corroboration of the Regression Modelvalues can be compared.

Received 31 July 2020 Revised 16 August 2020 Accepted 17 August 2020 Available online 31 August 2020 Timetabling, either course timetabling or examination timetabling is one of the major factor that influences the academic performance of any institutions. It’s a task that varies from one institution to another depending on the identified constraints. Timetabling is a constraint satisfaction problem whereby the primary goal is satisfying the amount of constraints as much as possible. The task of generating timetable is tedious, time consuming and getting a feasible timetable is not certain. This research work provides solution to the problem encountered in generating a timetable by designing and implementing a soft computing based course timetabling system using genetic algorithm. Genetic algorithm (GA) is one of soft computing techniques in solving optimization problems and is an adaptive heuristic search which is anchored on the principle of Darwin’s theory of natural selection and...

Soft computing approaches have different capabilities in error optimization for controlling the complex system parameters, Soft computing approaches provide a learning and design making support from the relevant datasets or others experts review experiences. Soft computing optimization approaches can be variety of many environmental and also stability related uncertainties. This paper explain the different soft computing approaches viz., Genetic algorithms, Fuzzy logics, results of different error optimization control case studies. Mathematical Models refer to the Conventional error optimization control , which define dynamic control Conventional controllers are often inferior to the intelligent controllers, due to lack in comprehensibility. The results that controllers provide better control on errors than conventional controllers. Hybridization of technique such as fuzzy logic with genetic algorithms etc., provide a better optimization control for the designing and developing of intelligent systems.