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Prior to the occurrence of an earthquake, the region undergoes intensive physiochemical changes. Such changes trigger degassing charge generation leading to positive change in the thermal regime and consequently creation of an earthquake preparation zone. These changes in thermal regime can be detected by the thermal sensors onboard various polar orbiting satellites. Recent researches have demonstrated that thermal infrared sensors onboard satellites (e.g., NOAA-AVHRR and Terra/Aqua-MODIS) can detect temporal transient thermal infrared anomalies prior to an earthquake. The paper presents satellite-based thermal observations associated with

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Abstract:The Equality-Generalized Travelling Salesman Problem (E-GTSP), which is an extension of the Travelling Salesman Problem (TSP), is stated as follows: given groups of points within a city, like banks, supermarkets, etc., find a minimum cost Hamiltonian cycle that visits each group exactly once. It can model many real-life combinatorial optimization scenarios more efficiently than TSP. This study presents five spatially driven search-algorithms for possible transformation of E-GTSP to TSP by considering the spatial spread of points in a given urban city. Presented algorithms are tested over 15 different cities, classified by their street-network's fractal-dimension. Obtained results denote that the R-Search algorithm, which selects the points from each group based on their radial separation with respect to the start-end point, is the best search criterion for any E-GTSP to TSP conversion modelled for a city street network. An 8.8% length error has been reported for this algorithm.

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