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Modeling and system performance analysis play an important role in the planning of air traffic system. In particular, this paper aims to concentrate on the modeling and the performance evaluation of air transportation system.

It has shown that system matrices inherent in the airspace network can be acquired based on the service times of flights. This paper deals with a logical modeling which can avoid temporal synchronization conflict of resources. As a result, a class of queuing system is investigated to obtain a representation of the airspace network dynamics using dioid model.

The analysis of the air traffic system is conducted by solving the system state model. This indicates that it is feasible to use eigenvalues of system model for acquiring characteristics of the considered air transport systems.

The departure scheduling prototype presented in this paper can offer air traffic controller a decision support tool to build optimal departure sequences for aircraft.

The properties of max-plus algebra described allow us to apply linear algebra concepts like eigenvalue and eigenvectors to obtain a solution to the air traffic system being modeled. By solving and analyzing the dioid model, this paper evaluated some performance measures of airspace network.

A number of automated tools will be required for the purpose of enabling efficient services in air traffic control. The purpose of this paper is to devise an optimal flight trajectory search method that optimizes airspace system efficiency for 3D space in the presence of uncertainties.

This paper put forward an optimization model for generating applicable solutions of multi-aircraft conflict resolution problem, and the solution is based on the principle of optimality.

The conflict resolution problem between multiple aircraft can be described by spatial discretization, and the approach taken digitizes the 3D space into a grid of nodes.

The simulation examples are given to illustrate the validity of trajectory search model and stress on the impact of different system parameters.

Realistic constraints that are convenient to operate are incorporated in the system model, and the results show that it can provide reliable decision-making for conflict avoidance.

Available literature claims that location is a key attribute in the housing market. However, the impact of this attribute is difficult to measure and the traditional hedonic approach using subjective assessments is problematic. This paper seeks to explore trend surface analysis technique, attempting to provide an alternative way to measure location values.

TSA works in a similar way to other response surface methods but it is implemented directly in regression models, using a set of combinations of the co‐ordinates of properties in several power degrees. It can also be implemented in artificial neural networks, taking advantage of the neural ability in non‐linear domains. This work presents a comparison between traditional regression approach, error modelling, response surfaces, and TSA. ANN is also used to estimate some models, comparing their results. The objective is to verify the behaviour of TSA in hedonic models. A case study was carried using data of over 30,000 sales tax data of apartments sold in Porto Alegre, a southern Brazilian town.

The results indicates that TSA is an effective tool for the spatial analysis of real estate, because TSA models are similar to other approaches, but are developed with less expert work.

This paper presents an application of TSA in real estate market, which is an interesting alternative to traditional measures of location attributes.