Narrow Results

Under the background of accelerating urbanization and increasing stress of ecological environment, the construction of livable city has attracted extensive attention and become a hot spot in the study of urban problems in the world. The evaluation of livable city is a reference for the comparison of urban development and also one of the evaluation criteria for the comparison of urban competitiveness. This paper focuses on three different evaluation factors of ecological environment, economic development and public service to construct an evaluation model of environmental quality of livable cities. Then particle swarm optimization (PSO) is introduced to optimize the parameters of support vector machine (SVM), and a SVM algorithm based on PSO (PSO-SVM) is proposed to solve the livable city evaluation model. Finally, the spatial analysis combined with ArcGIS software obtained the livable city evaluation and division results of Hunan Province. The results show that PSO-SVM algorithm is superior to SVM, BA-SVM, GA-SVM, and has the advantages of faster speed and higher classification accuracy.

On-site wastewater treatment facilities (WWTFs) collect, treat, and dispose wastewater from dwellings that are not connected to municipal wastewater collection and treatment systems. They serve about 25% of the total population in the United States from an estimated 26 million homes, businesses, and recreational facilities nationwide. There is currently no adequate coordinated information management system for on-site WWTFs. Given the increasing concern about environmental contamination and its effect on public health, it is necessary to provide a more adequate management tool for on-site WWTFs information. This paper presents the development of an integrated, GIS-based, on-site wastewater information management system, which includes three components: (1) a mobile GIS for field data collection; (2) a World Wide Web (WWW) interface for electronic submission of individual WWTF information to a centralized GIS database in a state department of public health or state environmental protection agency; and (3) a GIS for the display and management of on-site WWTFs information, along with other spatial information such as land use, soil types, streams, and topography. It is anticipated that this GIS-based on-site wastewater information management system will provide environmental protection agencies and public health organizations with a spatial framework for managing on-site WWTFs and assessing the risks related to surface discharges.

The state of the art in location models falls short to adapt to new requirements such as composition and integration of maps. Composing and integrating maps are typical operations we want to apply when we deal with ubiquitous computing applications because they evolve permanently (i.e. to add location information of new cities, buildings, means of transport, etc.). We propose a novel approach that by abstracting some concepts such as located objects and locations, can result in more flexible models, therefore allowing dynamic composition and integration of maps. With this approach, it is also possible to combine different location representations, making applications easier to extend.

A rectilinear map consists of a set of mutually non-intersecting rectilinear (i.e., horizontal or vertical) line segments, and each segment is allowed to use a rectangular label of height B and length the same as the segment. Sliding labels are not restricted to any finite number of predefined positions but can slide and be placed at any position as long as it intersects the segment. This paper considers three versions of the problem of labeling a rectilinear map with sliding labels and presents efficient exact and approximation algorithms for them.

Driven by the industrial challenge of labeling maps for GIS applications, we investigate the problem of computing a map region P such that a rectangular axis-parallel label L of a given size can be placed in it. The map region to be labeled is in general a non-convex n-gon which may contain holes. We first derive a new practical algorithm based on the sweep-line technique that determines the com set of Maximum Inscribed Rectangles (MIRs) in P in O(nk), where k is the size of the output, for the case when the polygon sides have an axis-parallel orientation. After the set of MIRs has been found, any subsequent query on label L placement runs in only O(logn) time. We then provide an algorithm to convert the general case to the axis-parallel case. Extensive experimentation in both laboratory and industrial settings confirms that the developed method is practical and highly efficient for processing large GIS data sets.

Among real-system applications of AI, the field of traffic simulation makes use of a wide range of techniques and algorithms. Especially, microscopic models of road traffic have been expanding for several years. Indeed, Multi-Agent Systems provide the capability of modeling the very diversity of individual behaviors. Several professional tools provide comprehensive sets of ready-made, accurate behaviors for several kinds of vehicles. The price in such tools is the difficulty to modify the nature of programmed behaviors, and the specialization in a single purpose, e.g. either studying resulting ows, or providing an immersive virtual reality environment. Thus, we advocate for a more exible approach for the design of multi-purpose tools for decision support. Especially, the use of geographical open databases offers the opportunity to design agent-based traffic simulators which can be continuously informed of changes in traffic conditions. Our proposal also makes decision support systems able to integrate environmental and behavioral modifications in a linear fashion, and to compare various scenarios built from different hypotheses in terms of actors, behaviors, environment and ows. We also describe here the prototype tool that has been implemented according to our design principles.

A digital city is a social information infrastructure for urban life (including shopping, business, transportation, education, welfare and so on). We started a project to develop a digital city for Kyoto based on the newest technologies including cooperative information agents. This paper presents an architecture for digital cities and shows the roles of agent interfaces in it. We propose two types of cooperative information agents as follows: (a) the front-end agents determine and refine users' uncertain goals, (b) the back-end agents extract and organize relevant information from the Internet, (c) Both types of agents opportunistically cooperate through a blackboard. We also show the research guidelines towards social agents in digital cities; the agent will foster social interaction among people who are living in/visiting the city.

This paper proposes a semi-automatic method of geographic information linking based on spatial relationships, entity names, entity categories and other features, combined with semantic and machine learning methods. First, we extracted geographic information from three geographic information sources: Open Street Map, Wikimapia, and Google places. The extracted geographic information is mainly for urban buildings in different regions. Secondly, we analyzed and extracted the characteristics of geographic information data to construct a geographic information ontology, and realized the integration of geographic data through the mapping of geographic information source data and geographic information ontology. Finally, the linking method of fusion classification algorithm support vector machine and K-nearest neighbor method are discussed separately. At the same time, it is compared with the linking method proposed by Samal et al. to comprehensively verify the accuracy of the method proposed in this paper from multiple angles, laying a good foundation for seismic information integration.

This article focuses on the integration of multicriteria decision analysis (MCDA) and geographical information systems (GIS) and introduces a tool, GIS–MCDA, written in visual basic in ArcGIS for GIS-based MCDA. The GIS–MCDA deals with raster-based data sets and includes standardization, weighting and decision analysis methods, and sensitivity analysis. Simple additive weighting, weighted product method, technique for order preference by similarity to ideal solution, compromise programming, analytic hierarchy process, and ordered weighted average for decision analysis; ranking, rating, and pairwise comparison for weighting and linear scale transformation for standardization can be applied by using this tool. The maximum score and score range procedures can be used for linear scale transformation. In this article also an application of the GIS–MCDA to determine the flood vulnerability of the South Marmara Basin in Turkey is examined. To check the validity and reliability of the results, the flood vulnerability layer is compared with flood-affected areas.

The ability or inability to develop an effective, reliable supplier network can often play a major role in determining an organization’s competitive position. Especially in today’s era of a complex global economy, disruptions to an organization’s supply chain can drastically undermine its ability to compete. We analyze the interaction between density risk, or risk related to the proximal relationships between suppliers, and environmental risk, or risk arising from conditions affecting a supplier’s local business environment. We provide a powerful supply base risk mitigation strategy incorporating spatial analytics to enhance our analyses. We develop a multi-objective program to manage these factors and recommend minimal risk supply bases. We detail the interaction between objectives in an example and discuss the ramifications for managers. This work will assist managers in their efforts to build a supply base that meets the cost and efficiency demands of their organization.

Rapid motorization and uncertainty in urban growth patterns make parking space management a serious task, especially in middle-income developing countries, and this has severe social, economic, and environmental repercussions including increased congestion, crash frequency, fuel and time consumption, and air pollution. Due to the complexity of the urban transportation issue and the wide variety of variables involved, a multicriteria assessment is essential. This study used fuzzy logic and geographical information systems (GIS) to develop a multi-criteria decision making (MCDM) model for managing parking in Shiraz’s central business district (CBD). The literature was mined for information on the variables that affect parking site placement, and a poll of experts ($n=11$) was used to determine their relative importance. The distance to travel attraction centers, distance to roads, land price, population density, and available land for multi-storey parking were among the factors considered. Meanwhile, the parking space shortage for each TAZ is calculated by subtracting the estimated parking space supply from the estimated parking space demand. An overlay of these two layers distinguishes locations that are in parking shortage zones and also meet multiple criteria. The results may aid policymakers in controlling parking demand by pinpointing the most promising places for investment.

Information systems (IS) and data analytics-focused academic disciplines remained surprisingly silent in attempting to contribute to a public understanding of critical societal challenges such as foreclosures. This paper tackles the gap by presenting a framework for building foreclosure prediction models by integrating publicly-available census-tract demographic data and readily-available technology (geographic IS (GIS) and machine learning (ML)). The framework is tested and validated using over 19,000 foreclosures from Cuyahoga County (OH) using J48 decision tree, artificial neural network, and Naive Bayes algorithms. The framework’s empirical test identifies nine critical demographic attributes to successfully predict foreclosures, confirming the findings of prior studies while offering several new, highly predictive variables that were missed by prior research. This research is a call to broader IS, CS, and data science communities to assist society in understanding critical societal issues that may need deploying and integrating more advanced technologies.

In classical artificial intelligence and machine learning fields, the aim is to teach a certain program to find the most convenient and efficient way of solving a particular problem. However, these approaches are not suitable for simulating the evolution of human intelligence, since intelligence is a dynamically changing, volatile behavior, which greatly depends on the environment an agent is exposed to. In this paper, we present several models of what should be considered, when trying to simulate the evolution of intelligence of agents within a given environment. We explain several types of entropies, and introduce a dominant function model. By unifying these models, we explain how and why our ideas can be formally detailed and implemented using object-oriented technologies. The difference between our approach and that described in other papers also — approaching evolution from the point of view of entropies — is that our approach focuses on a general system, modern implementation solutions, and extended models for each component in the system.

This chapter is devoted to aerospace images and raster topographic maps processing and recognition methods application to create and update vector maps and digital elevation models (DEMs), that form geoinformation basis to solve computational problems (for instance, relocation routes multicriterial construction) and visualize terrain.

Methods for objects with different geometric shapes detection in set up by user calibration points on aerospace images are considered. The method provides automatic detection of the object’s parameters (for instance, rectangle’s position, orientation, and aspect ratio). A method for buildings’ and constructions’ projection to the basement, providing their true geographic positions definition, and a method for objects’ shades detection, designed to calculate their heights over the underlying surface, are described. Experimental investigations of software instruments, created using mentioned above methods, are shown. Vectorization precision and velocity values compared to known analogs are presented.

Methods for isolines detection, height marks, and isolines’ signatures recognition on raster topographic maps, that were scanned from paper medium, and their composition to vector and digital elevation models are described. Experimental investigation results, namely, precision and velocity values, of DEM construction in automatic and automated modes are presented.

This paper studies a vehicle speed intelligent warning system, designs a vehicle safe running and intelligent control system with dynamic recognition and automatic control functions and establishes the architecture of the intelligent control system. This system judges the safe state of a vehicle automatically by comparing its real-time running speed with safe driving speed limit and then gives the vehicle driver a clue by releasing the vehicle speed warning information and finally controls the running speed by vehicle control module.

Forests are essential for survival and sustenance of life. Their growth should be optimized so that greater benefits are derived from them. With such a large establishment and geographical base, the monitoring and decision making becomes very critical. The inherent delays hamper the decision process required at a particular time. The increasing area covered by forest plantations creates a demand for trustworthy mechanisms to ensure they are responsibly established and managed. However, most are focused exclusively or prevalently on natural or semi-natural forests, while only a few are specific to planted forests or plantations. The main aim is to assess whether and to what extent planted forests are properly considered within the existing sets of standards/guidelines and to identify areas for improvements, is based on a series of comparative analysis. This paper focus to carry out the full potential of convergence of GIS and Mobile Technology for plantation, with emphasis on technically viable infrastructure solution based on sustainability principles. Integration of GIS and Mobile is being proposed with an objective to enable a single window access to information and services being provided by various formations and to establish a collaborated environment.