This work is part of a wider research project concerning waste system management, aimed to build a methodology able to support both planning and coordination and to provide some operative cues for integration of knowledge on waste system at the various territorial levels. The specific aim of this work is related to the individuation and quantification of Indicators of efficiency in the field of recyclable waste collection, that can be shared by local Autorithies and Service Managers in order both to develop the recyclable waste collection system and to increase the recyclable collected quantities of waste. To reach this aim, the study will test advanced model derived from Artificial Intelligence, able to extract the relations existing between the values assumed by the previously quoted Indicators, measuring the efficiency of recyclable-waste collection in a certain territory, and demographic and economic characteristics of population in the same territory. Once the previously quoted rules have been validated, they can be applied on data related to census areas (the smaller areas for which statistical data are available, containing a very small number of resident people, variable from 0 to 1000), in order to estimate, within each area, the values of recyclable-waste collection Indicators for different product categories. Extracted knowledge appears to be very useful for supporting both service managers in individuating sensitization policy, and local and territorial Autorithies in waste system planning at different territorial level.
Implementation of Artificial Intelligence Tools (KDD and MCA) to Support the Solid Waste Management Service in Tuscany: a Case Study
SANTINI, LUISA
2006-01-01
Abstract
This work is part of a wider research project concerning waste system management, aimed to build a methodology able to support both planning and coordination and to provide some operative cues for integration of knowledge on waste system at the various territorial levels. The specific aim of this work is related to the individuation and quantification of Indicators of efficiency in the field of recyclable waste collection, that can be shared by local Autorithies and Service Managers in order both to develop the recyclable waste collection system and to increase the recyclable collected quantities of waste. To reach this aim, the study will test advanced model derived from Artificial Intelligence, able to extract the relations existing between the values assumed by the previously quoted Indicators, measuring the efficiency of recyclable-waste collection in a certain territory, and demographic and economic characteristics of population in the same territory. Once the previously quoted rules have been validated, they can be applied on data related to census areas (the smaller areas for which statistical data are available, containing a very small number of resident people, variable from 0 to 1000), in order to estimate, within each area, the values of recyclable-waste collection Indicators for different product categories. Extracted knowledge appears to be very useful for supporting both service managers in individuating sensitization policy, and local and territorial Autorithies in waste system planning at different territorial level.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
