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UrbanSim
UrbanSim is an open source urban simulation system designed by Paul Waddell of the University of California, Berkeley and developed with numerous collaborators to support metropolitan land use, transportation, and environmental planning. It has been distributed on the web since 1998, with regular revisions and updates, frowww.urbansim.orgSynthicity Inc
coordinates the development of UrbanSim and provides professional services to support its application. The development of UrbanSim has been funded by several grants from the National Science Foundation, the U.S. United States Environmental Protection Agency, Environmental Protection Agency, the Federal Highway Administration, as well as support from states, metropolitan planning agencies and research councils in Europe and South Africa. Reviews of UrbanSim and comparison to other urban modeling platforms may be found in refe ...
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Simulation
A simulation is an imitative representation of a process or system that could exist in the real world. In this broad sense, simulation can often be used interchangeably with model. Sometimes a clear distinction between the two terms is made, in which simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Another way to distinguish between the terms is to define simulation as experimentation with the help of a model. This definition includes time-independent simulations. Often, computer simulation, computers are used to execute the simulation. Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games. Simulation is also used with scientific modelling of natural systems or human systems to gain insight into their functio ...
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Python (programming Language)
Python is a high-level programming language, high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. Python is type system#DYNAMIC, dynamically type-checked and garbage collection (computer science), garbage-collected. It supports multiple programming paradigms, including structured programming, structured (particularly procedural programming, procedural), object-oriented and functional programming. It is often described as a "batteries included" language due to its comprehensive standard library. Guido van Rossum began working on Python in the late 1980s as a successor to the ABC (programming language), ABC programming language, and he first released it in 1991 as Python 0.9.0. Python 2.0 was released in 2000. Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of ...
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Springfield, Oregon
Springfield is a city in Lane County, Oregon, Lane County, Oregon, United States. Located in the Willamette Valley, Southern Willamette Valley, it is within the Eugene-Springfield, OR MSA, Eugene-Springfield metropolitan statistical area. Separated from Eugene, Oregon, Eugene to the west, mainly by Interstate 5 in Oregon, Interstate 5, Springfield is the second-most populous city in the metropolitan area after Eugene. As of the 2020 United States Census, 2020 census, the city has a total population of 61,851, making it the List of cities in Oregon, ninth-most populous city in Oregon. The Briggs family first settled the Springfield area, arriving in 1848. The community was incorporated as a city in 1885. The city was named after a natural spring located in a field or prairie within the current city boundaries. For the majority of the 20th century, the economy of Springfield was largely dependent on the Oregon timber industry; since the 1990s, however, the economy has diversified, ...
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Agent-based Model
An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models. Particularly within ecology, ABMs are also called individual-based models (IBMs). A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used in many scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents ...
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Microsimulation
Microsimulation is the use of computerized analytical tools to perform analysis of activities such as highway traffic flowing through an intersection, financial transactions, or pathogens spreading disease through a population on the granularity level of individuals. Synonyms include microanalytic simulation and microscopic simulation. Microsimulation, with its emphasis on stochastic or rule-based structures, should not be confused with the similar complementary technique of multi-agent simulation, which focuses more on the behaviour of individuals. For example, a traffic microsimulation model could be used to evaluate the effectiveness of lengthening a turn lane at an intersection, and thus help decide whether it is worth spending money on actually lengthening the lane. Introduction Microsimulation can be distinguished from other types of computer modeling in looking at the interaction of individual ''units'' such as people or vehicles. Each unit is treated as an autonomous e ...
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Monte Carlo Method
Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. The name comes from the Monte Carlo Casino in Monaco, where the primary developer of the method, mathematician Stanisław Ulam, was inspired by his uncle's gambling habits. Monte Carlo methods are mainly used in three distinct problem classes: optimization, numerical integration, and generating draws from a probability distribution. They can also be used to model phenomena with significant uncertainty in inputs, such as calculating the risk of a nuclear power plant failure. Monte Carlo methods are often implemented using computer simulations, and they can provide approximate solutions to problems that are otherwise intractable or too complex to analyze mathematically. Monte Carlo methods are widely used in va ...
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Market Imperfection
In neoclassical economics, market failure is a situation in which the allocation of goods and services by a free market is not Pareto efficient, often leading to a net loss of economic value.Paul Krugman and Robin Wells (2006). ''Economics'', New York, Worth Publishers. The first known use of the term by economists was in 1958, Francis M. Bator (1958). "The Anatomy of Market Failure," ''Quarterly Journal of Economics'', 72(3) pp351–379(press +). but the concept has been traced back to the Victorian writers John Stuart Mill and Henry Sidgwick.Steven G. Medema (2007). "The Hesitant Hand: Mill, Sidgwick, and the Evolution of the Theory of Market Failure," ''History of Political Economy'', 39(3)pp. 331��358. 200Online Working Paper. Market failures are often associated with public goods, time-inconsistent preferences, information asymmetries, failures of competition, principal–agent problems, externalities, J.J. Laffont (2008). "externalities," ''The New Palgrave Dictionary o ...
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2008 Financial Crisis
The 2008 financial crisis, also known as the global financial crisis (GFC), was a major worldwide financial crisis centered in the United States. The causes of the 2008 crisis included excessive speculation on housing values by both homeowners and financial institutions that led to the 2000s United States housing bubble, exacerbated by predatory lending for subprime mortgages and deficiencies in regulation. Cash out refinancings had fueled an increase in consumption that could no longer be sustained when home prices declined. The first phase of the crisis was the subprime mortgage crisis, which began in early 2007, as mortgage-backed securities (MBS) tied to U.S. real estate, and a vast web of Derivative (finance), derivatives linked to those MBS, collapsed in value. A liquidity crisis spread to global institutions by mid-2007 and climaxed with the bankruptcy of Lehman Brothers in September 2008, which triggered a stock market crash and bank runs in several countries. The crisis ...
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Input-output Model
In computing, input/output (I/O, i/o, or informally io or IO) is the communication between an information processing system, such as a computer, and the outside world, such as another computer system, peripherals, or a human operator. Inputs are the signals or data received by the system and outputs are the signals or data sent from it. The term can also be used as part of an action; to "perform I/O" is to perform an input or output operation. are the pieces of hardware used by a human (or other system) to communicate with a computer. For instance, a keyboard or computer mouse is an input device for a computer, while monitors and printers are output devices. Devices for communication between computers, such as modems and network cards, typically perform both input and output operations. Any interaction with the system by an interactor is an input and the reaction the system responds is called the output. The designation of a device as either input or output depends on p ...
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Spatial Analysis
Spatial analysis is any of the formal Scientific technique, techniques which study entities using their topological, geometric, or geographic properties, primarily used in Urban design, Urban Design. Spatial analysis includes a variety of techniques using different analytic approaches, especially ''spatial statistics''. It may be applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, or to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures. In a more restricted sense, spatial analysis is geospatial analysis, the technique applied to structures at the human scale, most notably in the analysis of geographic data. It may also applied to genomics, as in Spatial transcriptomics, transcriptomics data, but is primarily for spatial data. Complex issues arise in spatial analysis, many of which are neither clearly defined nor completely resolved, but form the basis for current resear ...
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Deterministic Algorithm
In computer science, a deterministic algorithm is an algorithm that, given a particular input, will always produce the same output, with the underlying machine always passing through the same sequence of states. Deterministic algorithms are by far the most studied and familiar kind of algorithm, as well as one of the most practical, since they can be run on real machines efficiently. Formally, a deterministic algorithm computes a mathematical function; a function has a unique value for any input in its domain, and the algorithm is a process that produces this particular value as output. Formal definition Deterministic algorithms can be defined in terms of a state machine: a ''state'' describes what a machine is doing at a particular instant in time. State machines pass in a discrete manner from one state to another. Just after we enter the input, the machine is in its ''initial state'' or ''start state''. If the machine is deterministic, this means that from this point onwar ...
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