No. 17/2023

Online archive of Computer Science and Mathematical Modelling

No. 17/2023

1. Andrzej Ameljańczyk - Multi-aspect fuzzy sets in modelling the decision support systems

   Pages: 5 - 12
   Abstract: The paper presents the new mathematical modelling concept using the so-called multi-aspect fuzzy sets. The paper contains definitions of the most important characteristics of multi-aspect fuzzy sets in the context of their application in decision support algorithms. These include characteristics such as the image of the multi-aspect fuzzy set, the carrier and core, the bottom and top fronts of the fuzzy set, and many other characteristics derived from multi-criteria optimization. These concepts are illustrated with numerical examples.
   Keywords multi-aspect fuzzy set, global membership function, image of fuzzy set, lower and upper front of fuzzy set.
   Full article: 5_12_aameljanczyk_csmm_17_2023.pdf
2. Robert Jarosz - Proposition of multi-agent conflict situation simulation and reinforcement learning toolset with demonstration of early stage implementation

   Pages: 13 - 22
   Abstract: This paper introduces conceptual approach to modelling conflicts. A flexible framework compatible in development phase is presented. Model scalability, possibility of parallelization and computational distribution over network is discussed. As example of application there are presented two variants of classic game theory problems. At the end of the paper current problems are briefly stated and future work direction is presented.
   Keywords artificial intelligence, game theory, situation modeling, multi-agent conflict situations, rust.
   Full article: 13_22_rjarosz_csmm_17_2023.pdf
3. Khisal Wijesinghe, Suresh Perera, Chulanee Attanayake - Performance optimization through hybrid modelling: An application to dengue disease

   Pages: 23 - 27
   Abstract: Although, Dengue virus could be prevented through responsible human actions, it has become a serious threat to mankind. This study was intended to increase the prediction accuracy of dengue transmission using hybryd models. After forecasting with Grey Forecasting Model, Growth Curve Model, Alpha Sutte Indicator and Generalized Additive Model, the models with the best prediction accuracy were determined through lowest Mean Absolute Percentage Error (MAPE) recorded in error calculation. Accordingly, a hybrid model was developed, by using a weighted average method as a coupling technique. Through the calculations and the analysis carried out, Alpha Sutte Indicator and the Generalized Additive Model were chosen to develop the Hybrid Model. The model enhances the prediction accuracy for most of the regions in Sri Lanka. Forecasting dengue transmission accurately is important to allocate medical personnel and equipment, conduct effective environmental management and awareness programs and chemical vector controlling in correspondence to the rising figures of dengue patients.
   Keywords dengue transmission, generalized additive model, hybrid model.
   Full article: 23_27_kwijesinghe_csmm_17_2023.pdf
4. W.A.L. Niwanthi, H.D. Panditharathne, S.S.N. Perera - Solving sweeping problem for trees in graph theory

   Pages: 29 - 33
   Abstract: We develop a theory to determine the search number of a graph that allows us to detect an intruder along an edge without limiting the visibility of adjacent vertices. The presented technique here will allow to express the sweep problem as a linear program using an existing formulation of a linear program designed for problems where capture occurs only at a vertex of a graph. We also provide a method to solve the sweep problem for any complex tree, utilizing a set of sub-trees of the tree.
   Keywords Search and sweep problem, set covering problem, branch cut algorithm, homeomorphic trees.
   Full article: 29_33_niwanthi_solving_csmm_17_2023.pdf