MODEL TREE: AN APPLICATION IN REAL ESTATE APPRAISAL

In the last twenty years in real estate appraisal there has been a growing interest for new and reliable assessment techniques essentially through the introduction of pluriparametric estimate, in particular of linear regression. However, also these techniques seem having not a great deal of adherence to very complex markets, for which the detection of best suited techniques to investigate market segments is necessary. The aim of the research is to test the applicative possibilities of model tree to land market, in order to highlight possible market segments in the original data set not detectable a priori.data mining, model tree, multiple regression analysis, land market appraisal, Research Methods/ Statistical Methods, C01,

A two-step hybrid approach for modeling the nonlinear dynamic response of piezoelectric energy harvesters

An effective hybrid computational framework is described here in order to assess the nonlinear dynamic response of piezoelectric energy harvesting devices. The proposed strategy basically consists of two steps. First, fully coupled multiphysics finite element (FE) analyses are performed to evaluate the nonlinear static response of the device. An enhanced reduced-order model is then derived, where the global dynamic response is formulated in the state-space using lumped coefficients enriched with the information derived from the FE simulations. The electromechanical response of piezoelectric beams under forced vibrations is studied by means of the proposed approach, which is also validated by comparing numerical predictions with some experimental results. Such numerical and experimental investigations have been carried out with the main aim of studying the influence of material and geometrical parameters on the global nonlinear response. The advantage of the presented approach is that the overall computational and experimental efforts are significantly reduced while preserving a satisfactory accuracy in the assessment of the global behavior

Somewhere There Are Thousand Broken Hearts

https://digitalcommons.library.umaine.edu/mmb-vp/2510/thumbnail.jp

Model tree: An application in Real Estate Appraisal

In the last twenty years in real estate appraisal there has been a growing interest for new and reliable assessment techniques essentially through the introduction of pluriparametric estimate, in particular of linear regression. However, also these techniques seem having not a great deal of adherence to very complex markets, for which the detection of best suited techniques to investigate market segments is necessary. The aim of the research is to test the applicative possibilities of model tree to land market, in order to highlight possible market segments in the original data set not detectable a priori

Data mining in real estate appraisal: a model tree and multivariate adaptive regression spline approach

In this paper we adopt two exploratory modelling techniques: Model Trees and Multivariate Adaptive Regression Splines. The objective is the building of two sale price prediction models in order to highlight possible market segments not detectable a priori. We show how these novel procedures can help to understand complex patterns and interactions among predictors in real estate appraisal

A context-aware multiple Blockchain architecture for managing low memory devices

Blockchain technology constitutes a paradigm shift in the way we conceive distributed architectures. A Blockchain system lets us build platforms where data are immutable and tamper-proof, with some constraints on the throughput and the amount of memory required to store the ledger. This paper aims to solve the issue of memory and performance requirements developing a multiple Blockchain architecture that mixes the benefits deriving from a public and a private Blockchain. This kind of approach enables small sensors - with memory and performance constraints - to join the network without worrying about the amount of data to store. The development is proposed following a context-aware approach, to make the architecture scalable and easy to use in different scenarios

SOM-Based Approach for the Analysis and Classification of Synchronous Impulsive Noise of an In-Ship PLC System

The interest in wideband data transmission over power line communications has increased rapidly. This technology offers a convenient and inexpensive medium to transmit data, reducing the number of cables. This advantage is particularly appealing in many fields, like the railway, naval, and aeronautical ones. Nevertheless, several problems have to be faced to obtain a high data rate. In particular, the presence of noise makes the transmission difficult, degrading the quality of received signals and prohibiting the full application of these communication frameworks. In this paper the behaviour of an in-ship powerline communication system is analyzed in the presence of synchronous periodic impulsive noise. Such noise is modelled at source and its effects on the transmission of wideband signals are evaluated by means of a simulation circuit model. The obtained results allow to identify the characteristics of the channel and the critical conditions due to noise. Subsequently, an unsupervised technique based on principal component analysis and fuzzy c-mean classifier detects the presence and classifies the specific noises. Numerical results show that the proposed approach enables to achieve this target accurately under different operating conditions, proving to be an effective tool to enhance the performances of the considered technology

Pulses for healthy and sustainable food systems: The effect of origin on market price

Pulses are widely acknowledged for their high nutritional value due to high protein content, low content in calories, and low glycemic index; they are a good alternative to animal proteins thus offering a considerable number of social, environmental, and health benefits. Despite pulses being widely acknowledged as healthy and sustainable food, in mainly European countries, consumption is growing but still lower than the recommended level, production is unprofitable in comparison to the current market prices level, and a reduction in harvested area has led to a strong dependence on import for pulses supply. Pulses are particularly fitting to the feature of local food because they can be suitably grown in any context, even in the most complex areas, and consumer interest and awareness of food origin has strongly increased in recent years. Lentils were selected as a case study in this paper that aims to define which features are effective on market price and, in particular, the role of origin declaration on label plays in defining the market price and how the origin attributes may enhance market price and farms competitiveness. The methodological tool for this investigation is the hedonic price model, useful to explain the effects of attributes of pulses affecting the market price. Results contribute to a better understanding of the pulse market, emphasizing that the “origin declaration” on label may have a positive effect on market price