In this paper, a model based on Artificial Neural Network (ANN) has been applied to real estate appraisal. Moreover, an evaluation of ANN performances in estimating the sale price of residential properties has been carried out. Artificial Neural Networks (ANNs) are useful in modelling input-output relationships learning directly from observed data. This capability can be very useful in complex systems like the real estate ones where motivations, tastes and budget availability often do not follow rational behaviours. This study also analyses the impact of such key environmental conditions that represent a problem related to many industrial cities where pollution and landscaping consequences affect the real estate market and residential location choices. We have considered a set of asking price's houses collected in the urban area of Taranto (Italy) where the biggest European steel factory and the 2nd industrial harbour are located

Equity refers to a fair sharing of costs or resources. Horizontal equity concerns distribution among individuals or groups with the same necessities, whereas vertical equity should be considered in situations with different levels of needs. This paper deals with transit service, looking at how to make it equitable from a spatial and social point of view. Traditionally equity has been neglected in transit planning, being in the best cases an afterthought during service provision. Hence, we propose a methodology to plan and design public transport routes, which meets the needs of communities fostering equitable accessibility. In this paper we put forward a method to incorporate horizontal and vertical equity goals in a Transit Network Design Problem. We study how the costs of the system change with the attained level of equity and found that higher overall costs may be born if more equitable service provision has to be pursued.