Fuzzy modeling of user behaviors and virtual goods purchases in social networking platforms

An important aspect of managing social platforms, online games and virtual worlds is the analysis of user characteristics related to subscriptions and virtual goods purchases. The results of such a process could be adopted in decision support applications that build on top of users’ behavior provide efficient strategies for the virtual world’s management. One of the research questions in this area is related to the factors affecting purchases and their relation to the activity within social networks as well as the ability to use past data to make reasoning about future behaviors. Complex online systems are hard to analyze when adopting legacy methodologies due to the huge amount of data generated by users’ activity and changes in their behavior over time. In this paper, we discuss an analysis of the characteristics of users performing purchases for virtual products. We adopt a Neuro-Fuzzy system which has the ability to process data under uncertainty towards better decisions related to parameterization of the virtual retail system. The proposed Fuzzy Logic (FL) inference model focuses on the analysis of purchases based on the types of past transactions and social activity as inputs. The proposed system results values for specific parameters affecting/depicting users’ behavior like own purchases, gifting and virtual products usage as output. Our results could be adopted for decision support of online platform operators and show the relations between less and more experienced users in terms of frequency and value of purchases, engagement with the use of virtual goods and gifting behaviors. Models based on the social activity with distinguished inbound and outbound social connections show increased interest in virtual goods among users with a higher number of inbound connections as a possible tool for building social position. © J.UCS

Use of cellular automata for traffic analysis

Uniwersalność automatów komórkowych spowodowała, iż znajdują zastosowanie w wielu dziedzinach, np. w modelowaniu i symulacji ruchu drogowego. Autorzy prezentują dokonania w tym zakresie (tab. 1) oraz formułują nowy model, będący rozwinięciem modelu skrzyżowania dróg prezentowanego w [1] i [8]. Dodatkowo autorzy przedstawiają charakterystykę opracowanego, nowatorskiego systemu, umożliwiającego modelowanie dowolnego obszaru (zespół skrzyżowań i dróg) oraz symulowanie ruchu w ujęciu mikroskopowym.Cellular automata are considered by some researchers to belong to one of the IT department, which is an artificial intelligence. Even though their history goes back to the forties of the last century, much attention is still paid to the use of cellular automata for the process of testing and simulation of different phenomena. The universality of cellular automata caused their application to many areas such as: physics, computer graphics and traffic modeling. The authors present the achievements in this field (Table 1) and formulate a new traffic model which is a development of the crossroads model defined by Chowdhury-Schadschneider [1] and later by Bartodziej [8]. This new model helps to simulate traffic at the crossroads of two-lane and two-way roads. In addition, there is given the worked out system characteristics which enables modeling any area (intersections and roads) and carrying out the traffic simulations in a microscopic approach. The software consists of two applications: TrafficCA (traffic simulator based on cellular automata) and the map editor (this application enables generating any area including roads, traffic lights and the surroundings). Taking into account the fact that the simulated cases are always correct (carried out in accordance with properly defined models of cellular automata), the developed system, except for the traffic modeling, can be used for showing driver behaviour unfavourable for traffic capacity

Biogas and Biomethane Technologies: an AHP Model to Support the Policy Maker in Incentive Design in Italy

Over the past six years, biogas production in Italy has experienced an economic boom: more than 4.5 billion euro investments, about 2 billion normal cubic meters of natural gas equivalent produced. By contrast, biomethane production in Italy is not widespread. This limited spread substantially depends on the lack of profitable Government incentives to biomethane production. In the near future, the Italian Government is expected to fix new feed-in tariff (FIT) schemes for energy production by renewable energy sources (RES). In this context it is fundamental for the policy maker to identify whether it will be preferable to introduce more generous FITs to favor biogas production for electric power generation vs biomethane production through biogas upgrading. In this paper we propose a multi criteria decision model to support the policy maker in the definition of sustainable development policies for biogas and biomethane production. Specifically we provide an Analytic Hierarchy Process (AHP) model to multiple criteria prioritization of incentives paid to biogas vs biomethane. According to group decision making approaches, we selected a pool of experts that structured the decision problem and disaggregated it into a hierarchy by identifying quantitative and qualitative criteria and subcriteria to evaluate each technology. The model results reveal that biomethane production plants are preferred to biogas production plants independently from the size, whereas bigger size biomethane installations are ranked higher with respect to smaller ones. Under stringent public budget constraints it might be de facto inefficient and not cost-effective to introduce incentive mechanisms to biogas production plant