The Journal of New Mathematics & Natural Computing (ISSN: 1793-0057)

Description

With the maturity of linear and reductionist paradigms and the growing recognition of the importance of the new mathematics or the mathematics of uncertainty, this journal is devoted to the further development of the mathematics of uncertainty and its applications to computational, biological and social sciences. The very first example of the mathematics of uncertainty is probability and statistics, but we will not deal with this topic because it has well established societies. Our focus will be fuzzy sets and fuzzy logic, and newer mathematics of uncertainty yet to be discovered. So far as the application areas are concerned, we choose social science and biological science because their models, often involving vagueness and uncertainty are not yet fully understood, and the mathematics of uncertainty can play a crucial role. Furthermore, only the mathematics of uncertainty can provide approximate reasoning in decision making under multiple constraints and multiple criterion environment. The biologically-inspired, or natural, computing paradigm (e.g., genetic algorithm, differential evolution, and bioinformatics) has emerged as by far the most powerful strategy for hard, mathematically intractable problems.
This journal provides a public forum for sharing and exchanging ideas and research findings in the following four focused areas:

Mathematics of uncertainty: for modeling the vagueness and decision making, fuzzy set theory and fuzzy logic, encouraging the discovering of novel mathematics of uncertainty.
Social sciences applications: this journal has a long history of pioneering the applications of the mathematics of uncertainty in economics and finance, and more recently, applications in political science.
Naturally-inspired computing: this area also includes biologically-inspired system theory and computations. We also welcome research papers in pattern recognition and image processing using mathematics of uncertainty.
Computational brain research: includes traditional and cutting edge cognitive science research papers theoretical and experimental results as related to brain-like computing algorithms, pattern recognition using mathematics of uncertainty.
All of the above four areas can work together synergistically and grow together effectively. The emphasis of this journal is on quality, not quantity, and we believe in the importance of an interdisciplinary approach in advancing the state of the art.