A comparison study of two fuzzy-based decision visiting systems (FBDVSs) for sightseeing spots

Discovering and recommending points of interest are drawing more attention to meet the increasing demand from personalized tours. This paper aims to propose and evaluate two fuzzy-based systems for decision of sightseeing spots considering different conditions.

In the system, the authors considered four input parameters as follows: ambient temperature (AT), air quality (AQ), noise level (NL) and the current number of people (CNP) to decide the sightseeing spots visit or not visit (VNV). The authors call the proposed system: fuzzy-based decision visiting systems (FBDVSs). The authors implemented two systems as follows: FBDVS1 (three input parameters) and FBDVS2 (four input parameters). The authors make a comparison study between FBDVS1 and FBDVS2. The authors evaluate the proposed systems by computer simulations.

From the simulations results, the authors conclude that when CNP is increased, the VNV is increased. However, when AQ and NL are increased, the VNV is decreased. Also, when the AT is around 18°C-26°C, the VNV is the best. Comparing the complexity, the FBDVS2 is more complex than FBDVS1. However, FBDVS2 considers also the AT, which makes the system more reliable.

In the future, the authors would like to make extensive simulations to evaluate the proposed systems and compare the performance of the proposed systems with other systems.

By simulation results, the authors have shown that the proposed system has a good performance and can choose good sightseeing spots.