Satish Mohan

Effectiveness comparison of the residential property mass appraisal methodologies in the USA

Purpose - Quite a few statistical and artificial neural network (ANN) models have been developed for the mass appraisal of the real estate by the municipalities. The purpose of this paper is to report the results of a research conducted to compare the prediction accuracy of the three most used models: multiple regression model, additive nonparametric regression, and ANN. Design/methodology/approach - The three models were developed using the housing database of a town with 33,342 residential houses. In this database, the cutoff point for higher priced homes was

PRIORITY SCHEDULING OF URBAN REHABILITATION STREETS TO MINIMIZE CONGESTION, DELAYS, AND ACCIDENTS

88 per square foot of living area. Findings - The research confirmed that using statistical and ANN models are reliable and cost-effective methods for mass appraisal of residential housing. Originality/value - It was found that any of the three models can be used, with similar accuracy, for lower and medium-priced houses, but the ANN is considerably more accurate for higher priced houses.

Expert Systems Applications in Construction Management and Engineering

This paper describes the framework of a priority scheduling algorithm that minimizes traffic congestion, travel de lays, and accidents that occur during the rehabilitation of urban streets. The process utilizes: (i) GIS technology for storing and visualizing the necessary data of streets, and for applying traffic assignment, (ii) previous research on the costs of congestion, travel delays, and accident rates, and (iii) u tility theory for combining the values of the qualitative and quantitative attributes associated with road rehabilitation. The priority scheduling framework, developed in the research, has been applied to an example town with a population of 116,000, in which 10 street links were selected for repaving in 3 time phases, each of two months, during one construction season. By comparing the multi -attribute utilities of the three attributes using the proposed priority schedule, against the average multi -attribute utilities of 10 random time-schedules of the 10 streets (standard practice), the proposed construction scheduling algorithm yields a saving of 13 veh-hrs/hr in network travel time,

Total float management for delay analysis

127/hr in the cost of comfort and convenience, and 11 accidents per year. Further research is required for coding the proposed algorithm into an expert system that practitioners can easily learn to use and draw priority schedules for their road rehabilitation programs.