International Journal of Computing Science and Mathematics 

About: International Journal of Computing Science and Mathematics is an academic journal published by Inderscience Publishers. The journal publishes majorly in the area(s): Computer science & Algorithm. It has an ISSN identifier of 1752-5055. Over the lifetime, 250 publications have been published receiving 645 citations. The journal is also known as: IJCSM.

On a simple approach for Q-S synchronisation of chaotic dynamical systems in continuous-time

Abstract: In this paper, the problem of Q-S synchronisation for arbitrary dimensional chaotic dynamical systems in continuous-time is investigated. Based on nonlinear control method, we would like to present a constructive scheme to study the Q-S synchronisation between n-dimensional master chaotic system and m-dimensional slave chaotic system in arbitrary dimension. The new derived synchronisation result is proved using Lyapunov stability theory. In order to verify the effectiveness of the proposed method, our approach is applied to some typical chaotic systems and numerical simulations are given to validate the derived results.

Bifurcation and stability of a dynamical system with threshold prey harvesting

Abstract: In this study, a predator-prey interaction model with Holling type II functional response is studied. As the continuous threshold prey harvesting is introduced, the proposed model displays a dynami...

An improved cuckoo search algorithm for integer programming problems

Abstract: This paper presents a novel cuckoo search algorithm called elite opposition - cuckoo search algorithm (ECS) for solving integer programming problems. The opposite solution of the elite individual in the population is generated by an opposition-based strategy in the proposed algorithm and form an opposite search space by constructing the opposite population that locates inside the dynamic search boundaries, then, the search space of the algorithm is guided to approximate the space in which the global optimum is included by simultaneously evaluating the current population and the opposite one. The results show that ECS algorithm has faster convergence speed, higher computational precision and is more effective for solving integer programming problems.

On ve-degree molecular topological properties of silicate and oxygen networks

Abstract: Silicate based inorganic materials are important for the synthesis of a new inorganic molecules in which the studies for ultrahigh proton conductivity and catalysis. Quantitative structure-property and structure-activity relationships of the silicate oxygen networks necessitate expressions for the molecular topological features of these networks. In QSPR/QSAR studies, physicochemical characteristics and molecular topological indices such as atom-bond connectivity (ABC), geometric-arithmetic (GA), harmonic (H) and sum-connectivity (χ) indices are used to model the physicochemical properties of chemical compounds and networks. These topological indices are based on the degrees of the vertices (atoms) of a connected graph. Recently, two novel degree concepts have been defined in graph theory; ev-degrees and ve-degrees. In this study by using the ve-degree concept, we define ve-degree atom-bond connectivity (ve-ABC), ve-degree geometric-arithmetic (ve-GA), ve-degree harmonic (ve-H) and ve-degree sum-connectivity (ve-χ) indices as parallel to their corresponding classical degree versions. We show that the ve-degree sum-connectivity index give better correlation than Wiener, Zagreb and Randic indices to predict the acentric factor of octanes. Also, we compute the ve-degree topological indices for some silicate oxygen netwoks such as dominating oxide network (DOX), regular triangulene oxide network (RTOX), dominating silicate network (DSL) and derive analytical closed formulae of these networks.

Multi-objective classification based on NSGA-II

Abstract: The fast and elitist non-dominated sorting genetic algorithm-II (NSGA-II) is currently the most popular multi-objective evolutionary algorithm (MOEA). NSGA-II has been shown to work well for two-objective problems by attaining near-optimal diverse and uniformly distributed Pareto solutions. To use the powerful multi-objective optimisation performance of NSGA-II directly and conveniently, an optimisation classification model is presented. In the optimisation classification model, a linear equation set is constructed according to classification problems. In this paper, we introduced NSGA-II to solve the optimisation classification model. Besides, eight different datasets have been chosen in experiments to test the performance of NSGA-II. The results show that NSGA-II is able to find much better spread of solutions and has high classification accuracy and robustness.