Relevant bibliographies by topics / Input-output analysis Mathematical models

Academic literature on the topic 'Input-output analysis Mathematical models'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Input-output analysis Mathematical models"

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Vaninsky, Alexander. "Structural change optimization in input-output models." Journal of Interdisciplinary Mathematics 12, no. 6 (December 2009): 839–61. http://dx.doi.org/10.1080/09720502.2009.10700668.

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El-Demerdash, Basma E., Assem A. Tharwat, and Ihab A. A. El-Khodary. "A Unified Mathematical Model for Stochastic Data Envelopment Analysis." International Journal of Service Science, Management, Engineering, and Technology 12, no. 1 (January 2021): 127–41. http://dx.doi.org/10.4018/ijssmet.2021010108.

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Efficiency measurement is one aspect of organizational performance that managers are usually interested in determining. Data envelopment analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about the efficiency and performance of organizations and all sorts of functionally similar, relatively autonomous operating units. DEA models are either with a constant rate of return (CRS) or variable return to scale (VRS). Furthermore, the models could be input-oriented or output-oriented. In many real-life applications, observations are usually random in nature; as a result, DEA efficiency measurement may be sensitive to such variations. The purpose of this study was to develop a unified stochastic DEA model that handles different natures of variables independently (random and deterministic) and can be adapted to model both input/output-oriented problems, whether it is CRS or VRS. The chance-constrained approach was adopted to handle the stochastic variables that exist in the model. The developed model is implemented through an illustrative example.
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Zheng, Kai, and Yisheng Liu. "Application of Mathematical Models in Economic Variable Input and Output Models under the Scientific Visualization." Computational Intelligence and Neuroscience 2022 (February 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/6269358.

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At present, with the development of society and economy, some new problems have emerged continuously. Among them, the more serious problem is that enterprises pay too much attention to economic benefits, which leads to problems in the development of many enterprises. Therefore, the problem caused by too much emphasis on economic benefits is one of the major economic problems. After this problem, our country’s economy began to focus on economic input and output in the subsequent development process. And, related personnel have also studied the economic input-output technology and model, which is an economic quantitative analysis method that has been widely used in various aspects of the economic field since its emergence. This paper firstly elaborates the theoretical knowledge involved, such as economic data, economic variables, and visualization techniques. Secondly it analyzes the application of scientific visualization techniques in the processing of economic variable data, which includes the techniques of preprocessing, mapping, drawing, and displaying the data. Finally, this paper investigates the application of mathematical models in economic variables input and output and the application of mathematical models in economic research, which can help us to better understand and use the knowledge of economics, thus providing strong support for solving practical problems. Also, this helps people to understand and grasp more about the macroarea, microaspect, and even the country as a whole.
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Imai, Jun-ichi, Hiroyuki Shioya, and Masahito Kurihara. "Modeling and Analysis of Genetic Algorithms Based on the Viewpoint of Mixture Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 7, no. 3 (October 20, 2003): 268–75. http://dx.doi.org/10.20965/jaciii.2003.p0268.

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Some mathematical models have been proposed for theoretical analyses of genetic algorithms (GAs). However, these works have limited their objects to a few kinds of GAs in order to formulate them accurately. In this paper, we regard a GA as an information source that generates input-output data. That is, we regard a population and its next population generated by the GA as input and output respectively. Then we model the GA by learning from these data. Since this method uses only the input-output relations of data and ignores interior structures, we can describe a variety of GAs in a common form, and analyze them from a new point of view. We use some mixture models for a representation of these input-output relations in this paper. By using a mixture model for modeling a GA, we can represent the GA system as a combination of some partial systems. In this paper, we treat two types of mixture models, and investigate how these models are effective for analyzing GAs through some numerical experiments.
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Deng, Wei. "The Analysis of Energy and Environmental Efficiency Based on Input-Output Model." Applied Mechanics and Materials 34-35 (October 2010): 1253–57. http://dx.doi.org/10.4028/www.scientific.net/amm.34-35.1253.

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Input-output method can conveniently analyze energy consumption and environmental load for iron and steel enterprises. It can visually express production manufacturing statement and the consumption of energy and non-energy. Mathematical models are helpful for quantitative analysis and data handling. In addition, it’s useful to analyze main affected factors. Unit process energy consumption and steel ratio directly affect energy efficiency, which can be analyzed by e-p method.
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Shabani, Amir, Gholam Reza Faramarzi, Reza Farzipoor Saen, and Mohsen Khodakarami. "Simultaneous evaluation of efficiency, input effectiveness, and output effectiveness." Benchmarking: An International Journal 24, no. 7 (October 2, 2017): 1854–70. http://dx.doi.org/10.1108/bij-10-2015-0096.

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Purpose The purpose of this paper is to develop a data envelopment analysis (DEA) technique that simultaneously measures efficiency and effectiveness to provide a comprehensive appraisal of the productivity. Additionally, an algorithm is recommended to determine targets that are used for measuring effectiveness. Design/methodology/approach In this paper, for measuring productivity, a new methodology based on non-parametric mathematical DEA technique was presented. The proposed procedure is able to compute the efficiency input effectiveness, and output effectiveness, simultaneously. Findings By comparing with previous models, the authors’ proposed integrated model generates more detailed results and has more discriminating power. Originality/value To the best of the authors knowledge, there is not any study in which a non-parametric mathematical approach measures productivity through simultaneous combining of the effectiveness, including input effectiveness, and output effectiveness, and the efficiency.
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Vittal, B., Raju Nellutla, and M. Krishna Reddy. "Selection and Analysis of Input-Output Variables using Data Envelopment Analysis of Decision Making Units - Indian Private Sector Banks." International Journal of Engineering and Advanced Technology 10, no. 5 (June 30, 2021): 119–27. http://dx.doi.org/10.35940/ijeat.e2674.0610521.

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In banking system the evaluation of productivity and performance is the key factor among the fundamental concepts in management. For identify the potential performance of a bank efficiency is the parameter to evaluate effective banking system. To measure the efficiency of a bank selection of appropriate inputoutput variables is one of the most vital issues. The suitable identification of input-output variables helps to create and identify model in order to evaluate the efficiency and analysis. The Data Envelopment Analysis (DEA) is a mathematical approach used to measure the efficiency of identified Decision Making Units (DMUs). The DEA is a methodology for evaluating the relative efficiency of peer decision making units of identified input/output variables for the financial year 2018-19. In this study the basic DEA CCR, BCC models used for measure the efficiency of DMUs. In addition to these models for minimize the input excess and output shortfall Slack Based Measure (SBM) efficiency used. The SBM is a scalar measure which directly deals with slacks of input, output variables which help in obtain improved efficiency score compare with previous model. The result from the analysis is
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Novotny, V., H. Jones, X. Feng, and A. Capodaglio. "Time Series Analysis Models of Activated Sludge Plants." Water Science and Technology 23, no. 4-6 (February 1, 1991): 1107–16. http://dx.doi.org/10.2166/wst.1991.0562.

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Time series models of the activated sludge process are very useful in design and real time operation of wastewater treatment systems which deal with variable influent flows and pollution loads. In contrast to common deterministic dynamic mathematical models which require knowledge of a large number of coefficients, the time series models can be developed from input and output monitoring data series. In order to avoid “black box” approaches, time series models can be made compatible and identical in principle, with their dynamic mass balance model equivalents. In fact, these two types of models may differ only in nomenclature. ARMA-Transfer Function models can be used for systems which are linear or can be linearized such as typical BOD or suspended solids influent-effluent relationships for which the type of model is known. For systems which are highly nonlinear, and/or the input-output model is unknown, neural network models can be used. Both ARMA-TF models and neural network models can be made self-learning, that is, the performance of the model can be periodically improved manually or in an automated mode as new information is collected by monitoring. Application examples are included.
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Emmenegger, J. F., D. Chable, H. A. Nour Eldin, and H. Knolle. "Sraffa and Leontief Revisited: Mathematical Methods and Models of a Circular Economy." Cybernetics and Computer Technologies, no. 2 (July 24, 2020): 86–99. http://dx.doi.org/10.34229/2707-451x.20.2.9.

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Introduction. Sometimes new results in one scientific field can help to study quite other branches. In the new book we observe application of various mathematical methods to study circular economics. The purpose of the paper is to give information about the new book “SRAFFA AND LEONTIEF REVISITED: Mathematical methods and models of a circular economy”. The academic editor Walter de Gruyter-Oldenbourg has published this monography in January 2020 in English language. Results. This book contributes to the increasing call for a comprehensive perception of economic production processes. The book is dedicated to Wassily Leontief’s concept of Input-Output Analysis and to Piero Sraffa's seminal book “Production of Commodities by Means of Commodities”. Single product and joint production industries of a circular economy are described, consequently using matrix algebra. The central role of the Perron-Frobenius Theorem for non-negative matrices, specially Perron-Frobenius eigenvalues and eigenvectors is revealed as a common basis of Sraffa’s and Leontief’s approaches and applied to clarify the basic economic assumptions which are inherent to economic production processes. Conclusions. The book addresses young researchers wishing to explore the foundations of circular economy, practitioners wishing to examine the potential of Sraffa’s price models in connection to Leontief’s Input-Output analysis. Advanced undergraduate, graduate, PhD students and their instructors in economics, political science or applied mathematics, who seek to understand Sraffa and the recent developments of the circular economy of inter industrial and national economy will find numerous examples with complete solutions, presented by a rich, formal, mathematical methodology, revealing the economic content of the results. Detailed examples and visualizing graphs are presented for applications of various mathematical methods. Keywords: Input-Output analysis, circular economy, Perron-Frobenius Theorem, non-negative matrix.
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Stetsyuk, Petro, Maria Grygorak, Oleg Berezovskyi, and Oleksii Lykhovyd. "Mathematical Models of M.V. Mykhalevych for Forecasting Structural and Technological Changes." Cybernetics and Computer Technologies, no. 3 (November 29, 2022): 56–66. http://dx.doi.org/10.34229/2707-451x.22.3.6.

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Introduction. The identification of structural and technological disproportions that affect crisis phenomena in the economy and the analysis of ways to eliminate them require a wide application of quantitative research methods, in particular, mathematical modeling. “Input-Output” tables of Leontief turned out to be quite a convenient tool for analyzing these economic issues. In Leontief-type models, the matrix of technical coefficients (matrix of direct costs) is assumed to be known and calculated on the basis of statistical information from the “input-output” tables. M.V. Mykhalevych formulated the “inverse” problem: how to determine those structural and technological changes that would reduce the cost of production and thereby increase the incomes of end consumers and make the economy more dynamic. Or, in other words, how to choose or adjust technical coefficients to improve the properties of the economic process. This work is devoted to two optimization problems built on the basis of models of this type. The purpose of the article is to optimize the interdisciplinary planning of structural and technological changes. Results. Inverse models of the Leontief type for optimization of structural and technological transformations in economic systems are considered. These models are formulated in terms of nonlinear programming problems and include two objective functions for maximization: total consumer incomes and the “income growth–production growth” multiplier. Algorithms and software for solving these problems are presented. Numerical optimization procedures are based on Shor's r-algorithm. Conclusions. The use of inverse models of the Leontief type will allow choosing promising directions of structural and technological transformations in both the macro- and microeconomy. The proposed mathematical apparatus based on non-smooth optimization algorithms proved to be a sufficiently effective tool for solving appropriate optimization problems in practice. Keywords: structural and technological changes, inter-industry balance, Leontief model, “input-output” matrix, inverse Leontief-type models, non-smooth optimization algorithms, software.
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Dissertations / Theses on the topic "Input-output analysis Mathematical models"

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Siegel, Paul B. "The relationship between changing economic structure and performance: diversification, diversity, growth, stability, and distribution impacts." Diss., Virginia Tech, 1992. http://hdl.handle.net/10919/40017.

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Bailey, Robert Reid. "Input-output modeling of material flows in industry." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/19104.

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Carpentier, Line Chantal. "Agriculture and the environment : an economic-ecologic input-output model of the Canadian economy." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=55482.

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The current environmental movement calls for a re-evaluation of many economic-ecologic relationships. The objective of this study is to identify industrial sectors and final demands most responsible for particular types of residual discharge and resource use. An economic-ecologic model was constructed for the Canadian economy from the Statistics Canada I-O as modified by Thomassin et al. (1992). This modified version with its 12 agricultural sectors and 16 food processing sectors is best suited for agricultural policy analysis. The model estimates national erosion, pesticide and fertilizer use as well as air and water pollutants, solid waste, and water use associated with specified economic activities.
Two different scenarios were analyzed. In the first, the impact on both the economy and the environment from changes in the final demand for agricultural and food commodities was simulated. Each commodity's final demand was increased by $1 million and its impact compared to the other simulated results. The ten commodities studied yielded similar economic impacts, while their environmental impacts differed considerably. Changes in the demand for wheat and oilseeds had the largest environmental impacts.
In the second scenario, the effects of a $1 million increase in each final demand category were compared. This scenario focussed on markets rather than products. The construction, exports and personal expenditures categories were the greatest generator of wastes and the largest user of free resources. The exports category yielded twice as much erosion than personal expenditures and twenty times more than the next highest value (construction).
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Laurent, Sofie. "The mathematical justification of the Leontief and Sraffa input-output systems." Thesis, Uppsala universitet, Analys och sannolikhetsteori, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-374184.

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Butnar, Isabela. "Input-output analysis for use in life cycle assessment: introduction to regional modelling." Doctoral thesis, Universitat Rovira i Virgili, 2007. http://hdl.handle.net/10803/8589.

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The objective of this thesis is to study the combination of environmental Input-Output (IO) models with Life Cycle Inventory (LCI) into a common framework which allows for regional/national environmental analyses meanwhile conserving process details. Our results show that this is possible by "adapting" the two methods: compiling LCI in matrix form and disaggregating as much as possible the IO tables. Given the poor data availability for detailed analyses at regional/national level, the results of this work suggest starting with a "traditional" IO analysis together with a Structural Path Analysis to identify the most polluting sectors and the paths through which the pollution is propagated. For the identified most polluting sectors, LCA data should be collected and fed into a tiered-hybrid IO-LCA model which gives the regional picture meanwhile conserves process details.
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Rudolph, Frederick Marlow. "The evaluation of the effects of contrast versus numeric coding, redundancy, and density on input and output times." Thesis, Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/33438.

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Ren, Zhen. "Modular model assembly from finite element models of components." Diss., Connect to online resource - MSU authorized users, 2008.

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Cortés, Borda Daniel Enrique. "Contribution to the development of more efficient environmental policies via multi-objective optimization and environmentally extended input-output models." Doctoral thesis, Universitat Rovira i Virgili, 2014. http://hdl.handle.net/10803/283267.

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Al mercat globalitzat d’avui en dia la falta de coneixement sobre la distribució dels impactes entre els estats dificulta el disseny de polítiques efectives per la reducció, a escala global, de la degradació ambiental. L'objectiu d’aquesta tesi consisteix en la combinació de models macroeconòmics amb l’optimització multi-objectiu per facilitar la quantificació de càrregues ambientals, la distribució equitativa de responsabilitats i el disseny de polítiques públiques eficaces i sostenibles. Per aquest motiu aquí es proposen mètodes quantitatius basats en models input-output ampliats al medi ambient per estudiar la contribució de les nacions a les pressions ambientals globals, mitjançant l’estudi del cicle de vida dels productes que es consumeixen mundialment; les càrregues ambientals relacionades amb el comerç i l'equitat amb que es distribueixen els impactes. Els resultats poden ajudar a dissenyar polítiques eficaces per assegurar una justa assignació de responsabilitats. A més a més, aquesta tesi proposa un enfocament d'optimització multi-objectiu sistemàtic per minimitzar els impactes ambientals i, simultàniament, maximitzar la producció d’una economia. El model de programació lineal bi-criteri identifica els sectors clau que contribueixen significativament a l'impacte ambiental i que presenten una baixa producció econòmica. Els resultats mostren que amb les tecnologies existents i mitjançant un control adequat de la demanda dels sectors, els impactes ambientals es podrien reduir en major proporció que la producció econòmica. D’altra banda, aquesta tesi proposa un mètode basat en programació lineal per facilitar la presa de decisions en estudis ambientals de forma inversa. És a dir, donat un conjunt de solucions, aquest mètode obté els límits inferiors i superiors dels intervals dins dels quals els pesos de cada indicadors han de caure, de forma que l'alternativa seleccionada sigui òptima. D'aquesta manera, les persones encarregades de prendre decisions no estan obligades a proporcionar els pesos amb antelació, el que podria donar lloc a resultats esbiaixats.
En el mercado globalizado actual, la falta de conocimiento sobre cómo se distribuyen los impactos entre las naciones dificulta el diseño de políticas efectivas para la reducción, a escala global, de la degradación ambiental. El objetivo de esta tesis es combinar modelos macroeconómicos y optimización multiobjetivo para facilitar la cuantificación de cargas ambientales, la distribución equitativa de responsabilidades, y el diseño de políticas públicas eficaces que mejoren la sostenibilidad. Para ello, en esta tesis se proponen métodos cuantitativos basados en modelos input-output extendidos al medio ambiente para estudiar la contribución de las naciones a la presión ambiental global mediante el análisis del ciclo de vida de los productos que se consumen mundialmente, las cargas ambientales relacionadas con el comercio, y la equidad con que se distribuyen los impactos. Los hallazgos pueden ayudar a diseñar políticas eficaces para asegurar una asignación justa de responsabilidades. Además esta tesis propone un enfoque de optimización multiobjetivo sistemático para minimizar simultáneamente los impactos ambientales y maximizar la producción de una economía. El modelo de programación lineal bicriterio identifica los sectores clave que contribuyen significativamente al impacto y presentan una baja producción económica. Los resultados muestran que con las tecnologías existentes y controlando adecuadamente la demanda de ciertos sectores, los impactos ambientales podrían disminuir en mayor proporción que la producción económica. Además, esta tesis propone un método basado en programación lineal para facilitar la toma de decisiones ambientales mediante un análisis inverso. Es decir, dado un conjunto de soluciones, el método desarrollado busca los límites inferior y superior de los intervalos dentro de los cuales los pesos de cada indicador deben caer para que la alternativa seleccionada sea la óptima. De este modo, las personas encargadas de tomar decisiones no están obligadas a proporcionar los pesos de antemano, lo que podría conducir a resultados sesgados.
In today’s globalized market, the lack of knowledge about how the impacts distribute among nations hinders the design of effective policies for reducing the environmental degradation at a global scale. The aim of this thesis is to combine macroeconomic models with multi-objective optimization to facilitate the quantification of environmental loads, the fair allocation of responsibilities, and the design of effective public policies aiming at sustainability. To these end here we propose quantitative methods based on environmentally extended input-output models to study the contribution of nations to the global environmental pressures by examining the life cycle of products consumed worldwide; the trade-embodied environmental loads; and the equity with which impacts are distributed. Findings may help to design effective policies ensuring a fair allocation of responsibilities. This thesis also proposes a systematic multi-objective optimization approach for simultaneously minimizing the environmental impacts and maximizing the output of an economy. The bi-criteria linear programming model identifies key sectors with significant impact contribution and low output. Results show that, with the existing technologies, the environmental impacts could be lowered in higher proportion than the economic output by controlling adequately the demand of sectors. Moreover, this thesis proposes a method based on linear-programming to facilitate decision-making in environmental studies in an inverse manner. That is, given a set of solutions, this method finds the lower and upper limits of the intervals within which the weights to be attached to the indicators must fall, so that the selected alternative becomes optimal. Thereby, decision makers are not required to provide weights beforehand that could lead to biased results.
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Anderstig, Christer. "Applied Methods for Analysis of Economic Structure and Change." Doctoral thesis, Umeå universitet, Centrum för regionalvetenskap (CERUM), 1988. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-53044.

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The thesis comprises five papers and an introductory overview of applied models and methods. The papers concern interdependences and interrelations in models applied to empirical analyses of various problems related to production, consumption, location and trade. Among different definitions of 'structural analysis' one refers to the study of the properties of economic models on the assumption of invariant structural relations, this definition is close to what is aimed at in lire present case. Although the subjects cover widely differing aspects of the economic system, applied models and methods, i.e. entropy maximizing (information minimizing) models and random utility maximizing models, are in many cases closely connected. Tlic first paper reports on a regional input-ouput study applied to Norrbotten, Sweden. The paper is mainly concentrated on developing and estimating an econometric model, describing the structural interdependences in the Norrbotten economy. The chapter is composed of three parts. The first part concerns the theoretical basis of the model, the main fields of application and principal problems in connection with the estimation. The core of the estimated model is defined by the intersectoral dependences in the Norrbotten economy. This model can be viewed as a part of a more general model of the regional economy, and such a general model is briefly outlined. The second part reports on the collection and arranging of data, and the methods used for the estimation of the model. In the third part the results are presented. A special interest concerns the effects of production changes in the basic industries in the county, as to the expected impact on different industries and occupational groups. The second paper concerns some aspects of the problem of predicting trade flows in the forest sector. The model, based on information theory, is predicting current trade flows by adjusting the historical, a priori, trade flows to satisfy current export and import totals. In the third paper an entropy model is employed to decompose the interregional and intraregional employment change in Sweden and Stockholm, during the period 1960 - 1980, into effects attributed to regions (zones), industries, occupations and interaction effects. The fourth paper presents an empirical analysis of housing choice, based on individual data of households in Stockholm. The consumer choice is regarded as a complex choice from a finite set of discrete alternatives and a probabilistic choice mode! (multinomial logit) is employed, where secondary dwelling is included in the housing choice decision. In the final paper spectral analysis is used for identifying the significant components of cycle behaviour in time series of Swedish exports of forest products over a twenty year time period.
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Wieland, Hanspeter, and Stefan Giljum. "Carbon footprint decomposition in MRIO models: identifying EU supply-chain hot spots and their structural changes over time." WU Vienna University of Economics and Business, 2016. http://epub.wu.ac.at/5310/1/EcolEcon_WorkingPaper_2016_13.pdf.

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Politics' demand for informative consumption-based emission assessments based on multi-regional input output (MRIO) databases is steadily increasing. Based on the MRIO database EXIOBASE 3, we exemplify the utility of a range of analytical tools and discus their potential insights for consumption-based policies. The analysis decomposes the overall EU carbon footprint into product groups as well as into emitting regions. Subsequently, we illustrate the potential of applying production layer decomposition (PLD) and structural path analysis (SPA) for the assessment of global supply-chains related to the EU carbon footprint and their structural changes over time. We close with some policy ecommendations on reducing carbon footprint hot spots.
Series: Ecological Economic Papers
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Books on the topic "Input-output analysis Mathematical models"

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Karunaratne, Neil Dias. Australian development issues: An input-output analysis. Aldershot: Avebury, 1989.

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Pörting, Hermann Josef. Zeitlich verteilte Aktivität in der Input-Output-Analyse. Münster: Lit, 1987.

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Najnoviji razvoj u primjeni input-output analize: Strukturna analiza. Zagreb: Ekonomski in-t, 1993.

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Mezhotraslevye proport͡s︡ii obshchestvennogo proizvodstva: Problemy formirovanii͡a︡. Moskva: Ėkonomika, 1986.

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Ureña, Fernando A. Noriega. La desigualdad ingreso-producto en economía abierta: Su análisis en la perspectiva del modelo insumo-producto. México, D.F: Enfoques Editores, 1988.

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Pedersen, Ole Gravgård. Landbruget i amterne: En input-output analyse = Agriculture in the Danish counties : an input-output analysis. København: I kommission hos Landhusholdningsselskabets forlag, 1986.

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Lian, Wenrong. Tou ru xi shu ju zhen zhi gu ji yu tou ying. Taibei Shi: Cai tuan fa ren Zhonghua jing ji yan jiu yuan, 1994.

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Economic structure and maturity: Collected papers in input-output modelling and applications. Aldershot, Hants, England: Ashgate, 2000.

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Joaquín, Sermeño Lima, and Cortés Ortiz Rocío Areli, eds. La matriz de contabilidad social de Baja California Sur. La Paz: Universidad Autónoma de Baja California Sur, 2006.

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Holland, David. SAM multipliers: Their decomposition, interpretation and relationship to input-output multipliers. [Pullman?]: Washington State University, College of Agriculture and Home Economics Research Center, 1993.

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Book chapters on the topic "Input-output analysis Mathematical models"

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Wen, Fengan. "Retracted: A Mathematical Model for Higher Education Input–Output Efficiency Analysis." In Lecture Notes in Electrical Engineering, 679–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35440-3_87.

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Wen, Fengan. "Erratum to: A Mathematical Model for Higher Education Input–Output Efficiency Analysis." In Lecture Notes in Electrical Engineering, E1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35440-3_98.

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Quinby, Francis, Seyeon Kim, Sohee Kang, Marco Pollanen, Michael G. Reynolds, and Wesley S. Burr. "Markov Transition Matrix Analysis of Mathematical Expression Input Models." In Lecture Notes in Computer Science, 451–61. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52200-1_45.

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Nyhus, Douglas. "The INFORUM—ERI international system of macroeconomic input—output models." In Input-Output Analysis, 391–410. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2607-3_22.

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Dawson, John, Anna Gams, Ivan Rajen, Andrew M. Soltisz, and Andrew G. Edwards. "Computational Prediction of Cardiac Electropharmacology - How Much Does the Model Matter?" In Computational Physiology, 51–62. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05164-7_5.

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AbstractAnimal data describing drug interactions in cardiac tissue are abundant, however, nuanced inter-species differences hamper the use of these data to predict drug responses in humans. There are many computational models of cardiomyocyte electrophysiology that facilitate this translation, yet it is unclear whether fundamental differences in their mathematical formalisms significantly impact their predictive power. A common solution to this problem is to perform inter-species translations within a collection of models with internally consistent formalisms, termed a “lineage”, but there has been little effort to translate outputs across lineages. Here, we translate model outputs between lineages from Simula and Washington University for models of ventricular cardiomyocyte electrophysiology of humans, canines, and guinea pigs. For each lineage-species combination, we generated a population of 1000 models by varying common parameters, namely ion conductances, according to a Guassian log-normal distribution with a mean at the parameter’s species-specific default value and standard deviation of 30%.We used partial least squares regression to translate the influences of one model to another using perturbations to calculated descriptors of resulting electrophysiological behavior derived from these parameter variations. Finally, we evaluated translation fidelity by performing a sensitivity analysis between input parameters and output descriptors, as similar sensitivities between models of a common species indicates similar biological mechanisms underlying model behavior. Successful translation between models, especially those from different lineages, will increase confidence in their predictive power.
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Cichocki, Krzysztof, and Waldemar Wojciechowski. "Investment coefficient matrix in dynamic input—output models: an analysis and prognosis." In Input-Output Analysis, 231–52. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2607-3_15.

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Sand, Paal. "The use of impact tables for policy applications of input—output models." In Input-Output Analysis, 263–86. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2607-3_17.

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Treyz, George I. "Regional Input-Output Models." In Regional Economic Modeling: A Systematic Approach to Economic Forecasting and Policy Analysis, 263–90. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-017-2874-4_6.

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Tan, Raymond R., Kathleen B. Aviso, Michael Angelo B. Promentilla, Krista Danielle S. Yu, and Joost R. Santos. "Mathematical Foundations of Input–Output Models." In Lecture Notes in Management and Industrial Engineering, 9–28. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1873-3_2.

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Steffens, Franz. "Some Remarks on Relational Input-Output-Models." In Mathematical Modelling in Economics, 464–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78508-5_45.

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Conference papers on the topic "Input-output analysis Mathematical models"

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Zolock, John, and Robert Greif. "Application of Time Series Analysis and Neural Networks to the Modeling and Analysis of Forced Vibrating Mechanical Systems." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-55519.

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A theoretical and mathematical based methodogy is discussed that utilizes time series analysis techniques and neural networks to model forced vibrating mechanical systems using measured input-output data. A technique in nonlinear time series analysis known as phase space reconstruction may be used to extend our understanding of the active dynamics recorded in a single time series measurement. Using a recorded output (response) measurement phase space reconstruction parameters are calculated; the embedding dimension is estimated using the method of false nearest neighbor, and the time delay is estimated from the first minimum of the mutual information. The phase space reconstruction characteristics are then used to fully shape the architecture of a time delayed neural network model for the dynamical system. The modeling methodology is applied to several forced vibrating systems common to many fields of engineering. The neural models are then used to analyze new input, demonstrating the usefulness and importance of the methodology.
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Baturin, Oleg, Grigorii Popov, Paúl Nicolalde, and Anastasia Korneeva. "Identification of the Mathematical Model of a Gas Turbine Engine Taking Into Account the Uncertainty of the Initial Data." In ASME 2021 Gas Turbine India Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gtindia2021-76018.

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Abstract The article describes the method developed by the authors and tested on the example of the AI-25 engine. The study was focused on determining the probability distribution of the output parameters of a gas turbine engine mathematical model. The distribution was obtained considering the uncertainty of the initial data. The paper describes the identified problems and possible ways to solve them. In particular, it was found that it is not possible to study the influence of more than 7..8 input parameters on the probability distribution of output parameters with the current level of development of computer technology even using simple mathematical models. For this reason, a method has been developed to obtain reliable results while reducing the number of considered input data based on sensitivity analysis. The paper also proposed a way of comparing stochastic experimental and computational data with each other using a bivariate distribution. This method allows a precise characterisation of the calculation error using 4 numerical values. The experience obtained in the work has shown that taking into account the uncertainty of the initial data dramatically changes the process of interpreting the results. It should be noted that the obtained results are universal and can be used with other mathematical models in various industries although they were developed on the example of the mathematical model of a gas turbine engine.
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Gruden, Chiara, Irena Ištoka Otković, and Matjaž Šraml. "Selection and analysis of input parameters influencing pedestrian micro-simulated crossing time." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.1017.

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Pedestrian unrestrained behaviour, sudden movements and vulnerability are elements, which can highly affect road safety, especially when interacting with motorized vehicles. Therefore, it is important to have a deep insight in pedestrian behaviour. A way to tackle this issue is micro-simulation. Modern micro-simulation tools, indeed, allow, thanks to the implemented mathematical formulation of the problem, to model and repeat a real situation in a virtual environment. Nevertheless, they need to well-fit the real observed behaviour: the calibration step allows to make the model reliable, by adapting selected, influential model input parameters. By dealing with pedestrian issues, software Vissim/Viswalk has been selected for micro-simulation, which implements Helbing's Social Force model. This model is based on several parameters, like relaxation time, side preference, strength and range of pedestrian interactions, amount of anisotropy, parameters governing the forces among pedestrians, noise, number of reacting pedestrians, queue order and straightness, which need to be set by the user when creating the model, but they can be hardly measured. This paper presents a selection of the recalled input parameters, on which statistical tests are carried out to understand their influence on the behavioural output – crossing time - that is supposed to describe pedestrian crossing behaviour. This is the first step towards the development of a new calibration methodology, which will keep advantage of artificial intelligence tools to fine-tune micro-simulation input parameters.
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Shahidi, Parham, Steve C. Southward, and Mehdi Ahmadian. "Fuzzy Analysis of Speech Metrics to Estimate Conductor Alertness." In ASME 2009 Rail Transportation Division Fall Technical Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/rtdf2009-18031.

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A Fuzzy Logic-based algorithm has been developed for processing a series of speech metrics with the ultimate goal of estimating train conductor alertness. The output is a single metric, which directly quantifies the alertness level of the conductor. The metrics were selected based on their correlation to alertness through processed speech, but without any interpretation of the spoken words or phrases. Metrics that are used include: speech duration, silence duration, word production rate and word intensity. The assessment of these metrics is an experience and human knowledge based task, which generates the need for a mathematical model to accommodate this special circumstance. The algorithm developed here uses Fuzzy Logic to cast the human knowledge base into a mathematical framework for the alertness estimation analysis. The core of this fuzzy system is a rule base consisting of fuzzy IF-THEN rules, which are derived from the existing knowledge about the effects of sleep deprivation on alertness such as Furthermore, the rules were inferred from actual voice recordings that were taken on board a train. This data was then used to create a classification scheme to determine which pattern in the speech indicates different levels of alertness from anxiety to fatigue. The simplicity of the underlying mathematical model in this approach enables this system to compute and output an alertness metric in real-time. The nature of this algorithm allows for the use of an arbitrary number of rules to classify the alertness level and therefore provides the ability to continuously develop and extend the rule base as new knowledge emerges. The resulting algorithm is a fast, multi-input, single-output system that is able to quantify the train conductor’s alertness level anytime speech is produced.
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Cho, Hyunkyoo, K. K. Choi, and David Lamb. "Confidence-Based Method for Reliability-Based Design Optimization." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34644.

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An accurate input probabilistic model is necessary to obtain a trustworthy result in the reliability analysis and the reliability-based design optimization (RBDO). However, the accurate input probabilistic model is not always available. Very often only insufficient input data are available in practical engineering problems. When only the limited input data are provided, uncertainty is induced in the input probabilistic model and this uncertainty propagates to the reliability output which is defined as the probability of failure. Then, the confidence level of the reliability output will decrease. To resolve this problem, the reliability output is considered to have a probability distribution in this paper. The probability of the reliability output is obtained as a combination of consecutive conditional probabilities of input distribution type and parameters using Bayesian approach. The conditional probabilities that are obtained under certain assumptions and Monte Carlo simulation (MCS) method is used to calculate the probability of the reliability output. Using the probability of the reliability output as constraint, a confidence-based RBDO (C-RBDO) problem is formulated. In the new probabilistic constraint of the C-RBDO formulation, two threshold values of the target reliability output and the target confidence level are used. For effective C-RBDO process, the design sensitivity of the new probabilistic constraint is derived. The C-RBDO is performed for a mathematical problem with different numbers of input data and the result shows that C-RBDO optimum designs incorporate appropriate conservativeness according to the given input data.
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Burton, R., J. Ruan, P. Ukrainetz, and D. Bitner. "Analysis of Electromagnetic Nonlinearities in Stage Control of a Stepper Motor and Spool Valve." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-39342.

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In digital valves, stepper motors are often used as the electro-to-mechanical interface. To sustain both high speed of response and good quantitative accuracy, a special algorithm has been designed to control the stepper motor to produce a continuous displacement. Unlike conventional proportional magnets or torque motors, the input current to the stepper motor is cyclic (stage control) which has been shown to reduce magnetic saturation and hysteresis. In this paper a special mathematical formulation is developed to simulate magnetic saturation and hysteresis which can be applied to a generic situation. The mathematical formulation derived is one in which hysteresis and saturation parameters are established; an error rate of both saturation and hysteresis is defined from this. Since the error rates are easily determined experimentally or through manufacturers’ specifications, the parameters can be found from these mathematical formulations. The parameters can then be used to predict the hysteresis and saturation characteristics. Special experiments are designed to obtain the input-output characteristics of a stepper motor/valve system under single and multi-stage control. The model follows the experimental results reasonably well and can be used with confidence to model any system with hysteresis and saturation. The model also predicts very well the effects of using stage control in reducing hysteresis and saturation in a practical valve.
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Chen, Wei, Ruichen Jin, and Agus Sudjianto. "Analytical Variance-Based Global Sensitivity Analysis in Simulation-Based Design Under Uncertainty." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57484.

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The importance of sensitivity analysis in engineering design cannot be over-emphasized. In design under uncertainty, sensitivity analysis is performed with respect to the probabilistic characteristics. Global sensitivity analysis (GSA), in particular, is used to study the impact of variations in input variables on the variation of a model output. One of the most challenging issues for GSA is the intensive computational demand for assessing the impact of probabilistic variations. Existing variance-based GSA methods are developed for general functional relationships but require a large number of samples. In this work, we develop an efficient and accurate approach to GSA that employs analytic formulations derived from metamodels of engineering simulation models. We examine the types of GSA needed for design under uncertainty and derive generalized analytical formulations of GSA based on a variety of metamodels commonly used in engineering applications. The benefits of our proposed techniques are demonstrated and verified through both illustrative mathematical examples and the robust design for improving vehicle handling performance.
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Shih, Yi-Pei, Bor-Tyng Sheen, Kun-Yu Wu, and Jyh-Jone Lee. "Transmission Errors and Backlash Analysis of a Single-Stage Cycloidal Drive Using Tooth Contact Analysis." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85558.

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Cycloidal gear drives possess compact sizes, large reduction ratios, and low backlash. They are particularly suitable for applications in precise positioning and large output torque, for example, industrial robots and machine tools. Two main dynamic performances, transmission accuracy and backlash, is directly influenced by manufacturing errors. This paper aims to provide a direct method to effectively evaluate both performances. The mathematical models of transmission errors and backlash are established using the theory of gearing as well as tooth contact analysis. Three cases, considering profile modifications of the cycloidal gear and manufacturing errors, are evaluated to verify the correctness of the mathematical models.
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Shi, Yan, Tiecheng Wu, Andrew R. Plummer, and Maolin Cai. "The Flow Dynamics of an Air-Driven Hydraulic Pump." In ASME/BATH 2015 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/fpmc2015-9570.

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Air-driven hydraulic pumps are widely used to pump high-pressure oil for small hydraulic systems, where it is uneconomic to set up a conventional hydraulic power pack. To obtain good performance of a small hydraulic system, input air flow and output oil flow characteristics of the air-driven hydraulic pump should be properly understood. In this paper, based on a mathematical model which has been experimentally verified, the model of an air-driven hydraulic pump is proposed. Using the software MATLAB/Simulink for simulation, the dynamic characteristics of the pumps are obtained. To set a foundation for the optimization of the pump, the influence of key parameters on the output characteristics of the pump was studied. Through analysis, it can be obtained that, firstly, with an increase in the input air pressure, output oil pressure and area ratio, the ratio of output to input volume flow rate decrease approximately linearly. Moreover, when the output oil pressure was fixed, an energy-saving method to enhance the output oil flow is to enlarge the area ratio of the pump. Furthermore, the output oil flow can be increased rapidly through increasing the input air pressure, but that may result in an increase in compressed air consumption. This research is of use in the performance and design optimization of air-driven hydraulic pumps.
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Ma, Xiao Qing, Vikram Chopra, Jorge Angeles, and Martin Asger Haugaard. "Testbed of a Novel Robotic Pitch-Roll Wrist for Parameter Identification: Modeling and Analysis." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86551.

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The paper reports work in progress on the development of an innovative gearless pitch-roll wrist (PRW) for robotic applications. The PRW bears the morphology of a bevel-gear differential, its novelty lying in the absence of gears. Indeed, the PRW motivating this study is based on cams and rollers, intended to overcome the drawbacks of their bevel-gear counterparts—backlash, Coulomb friction and low stiffness. A testbed designed for parameter identification is introduced here. The paper discusses the mathematical modeling of the testbed, starting from its iconic model. The mathematical model is used to obtain the frequency response of the whole testbed, regarded as a multiple-input-multiple-output system, under the assumption that the parts of the spherical epicyclic train are rigid. The numerical values for the inertia parameters used in the model were taken from CAD models, those for stiffness and damping, as yet unknown, were estimated from a similar testbed reported elsewhere. The work ahead targets the experimental derivation of the Bode plots of the testbed, from which the numerical values of its inertia, stiffness and damping parameters are to be estimated. Moreover, having computed the stiffness and damping parameters of the testbed, the next step will be to drive the PRW at high frequencies, of the order of 1 kHz, to enable the identification of the stiffness and damping parameters of the PRW proper.
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Reports on the topic "Input-output analysis Mathematical models"

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Clausen, Jay, Christopher Felt, Michael Musty, Vuong Truong, Susan Frankenstein, Anna Wagner, Rosa Affleck, Steven Peckham, and Christopher Williams. Modernizing environmental signature physics for target detection—Phase 3. Engineer Research and Development Center (U.S.), March 2022. http://dx.doi.org/10.21079/11681/43442.

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The present effort (Phase 3) builds on our previously published prior efforts (Phases 1 and 2), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried object detection. Environmental phenomenological effects are often represented in weather forecasts in a relatively coarse, hourly resolution, which introduces concerns such as exclusion or misrepresentation of ephemera or lags in timing when using this data as an input for the Army’s Tactical Assault Kit software system. Additionally, the direct application of observed temperature data with weather model data may not be the best approach because metadata associated with the observations are not included. As a result, there is a need to explore mathematical methods such as Bayesian statistics to incorporate observations into models. To better address this concern, the initial analysis in Phase 2 data is expanded in this report to include (1) multivariate analyses for detecting objects in soil, (2) a moving box analysis of object visibility with alternative methods for converting FLIR radiance values to thermal temperature values, (3) a calibrated thermal model of soil temperature using thermal IR imagery, and (4) a simple classifier method for automating buried object detection.
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Shabelnyk, Tetiana V., Serhii V. Krivenko, Nataliia Yu Rotanova, Oksana F. Diachenko, Iryna B. Tymofieieva, and Arnold E. Kiv. Integration of chatbots into the system of professional training of Masters. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4439.

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The article presents and describes innovative technologies of training in the professional training of Masters. For high-quality training of students of technical specialties, it becomes necessary to rethink the purpose, results of studying and means of teaching professional disciplines in modern educational conditions. The experience of implementing the chatbot tool in teaching the discipline “Mathematical modeling of socio-economic systems” in the educational and professional program 124 System Analysis is described. The characteristics of the generalized structure of the chatbot information system for investment analysis are presented and given: input information, information processing system, output information, which creates a closed cycle (system) of direct and feedback interaction. The information processing system is represented by accounting and analytical data management blocks. The investment analysis chatbot will help masters of the specialty system analysis to manage the investment process efficiently based on making the right decisions, understanding investment analysis in the extensive structure of financial management and optimizing risks in these systems using a working mobile application. Also, the chatbot will allow you to systematically assess the disadvantages and advantages of investment projects or the direction of activity of a system analyst, while increasing interest in performing practical tasks. A set of software for developing a chatbot integrated into training is installed: Kotlin programming, a library for network interaction Retrofit, receiving and transmitting data, linking processes using the HTTP API. Based on the results of the study, it is noted that the impact of integrating a chatbot into the training of Masters ensures the development of their professional activities, which gives them the opportunity to be competent specialists and contributes to the organization of high-quality training.
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Dutta, Soumya, Jonathan Lee Woodring, and James Paul Ahrens. Uncertainty, sensitivity, and error analysis and visualization of high-dimensional Input-output models. Office of Scientific and Technical Information (OSTI), September 2017. http://dx.doi.org/10.2172/1392895.

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Blundell, S. User guide : the DEM Breakline and Differencing Analysis Tool—gridded elevation model analysis with a convenient graphical user interface. Engineer Research and Development Center (U.S.), August 2022. http://dx.doi.org/10.21079/11681/45040.

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Gridded elevation models of the earth’s surface derived from airborne lidar data or other sources can provide qualitative and quantitative information about the terrain and its surface features through analysis of the local spatial variation in elevation. The DEM Breakline and Differencing Analysis Tool was developed to extract and display micro-terrain features and vegetative cover based on the numerical modeling of elevation discontinuities or breaklines (breaks-in-slope), slope, terrain ruggedness, local surface optima, and the local elevation difference between first surface and bare earth input models. Using numerical algorithms developed in-house at the U.S. Army Engineer Research and Development Center, Geospatial Research Laboratory, various parameters are calculated for each cell in the model matrix in an initial processing phase. The results are combined and thresholded by the user in different ways for display and analysis. A graphical user interface provides control of input models, processing, and display as color-mapped overlays. Output displays can be saved as images, and the overlay data can be saved as raster layers for input into geographic information systems for further analysis.
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McKinnon, Mark, Daniel Madryzkowksi, and Craig Weinschenk. Development of a Database of Contemporary Material Properties for Fire Investigation Analysis - Materials and Methods. UL Firefighter Safety Research Institute, July 2020. http://dx.doi.org/10.54206/102376/zmpa6638.

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Meetings with the majority of the Technical Panel for the Development of an Interactive Database of Contemporary Material Properties for Fire Modeling project were held on June 29 and June 30, 2020. The major subjects of discussion included the list of proposed materials to be tested and characterized, the properties for the database, and the experimental and analytical methods to determine the properties for the database. A list of 101 materials divided into 11 categories were identified for inclusion in the database. The topics of variability in materials and aging of products and furniture items was discussed and it was concluded that investigating these variations is outside the scope of the project in this phase. The list of properties to be stored in the database for each material as well as proposed experimental methods to determine each property were discussed in the Technical Panel meetings. The discussion emphasized that the priorities for the properties represented in the database are dependent on the expected users for the database. Three potential user groups and the sets of properties that each group would likely require were identified. To ensure that the data contained in the database is useful for modeling, it was determined that prioritization would be given to complete sets of properties to be measured and stored in the database. Over the course of the two meetings, several tools were proposed to make the database easier for model practitioners to use. Once such tool included functionality to output lines of code for the models or entire model input files to simplify the process of inserting the properties into computa- tional fire models. Another tool that was discussed would involve automatically extracting derived properties from data sets or translating between complex and simple representations of burning. The next phase of the project includes conducting research to finalize the structure of the database and finalizing experimental procedures and protocols to populate the database.
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Warrick, Arthur W., Gideon Oron, Mary M. Poulton, Rony Wallach, and Alex Furman. Multi-Dimensional Infiltration and Distribution of Water of Different Qualities and Solutes Related Through Artificial Neural Networks. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7695865.bard.

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The project exploits the use of Artificial Neural Networks (ANN) to describe infiltration, water, and solute distribution in the soil during irrigation. It provides a method of simulating water and solute movement in the subsurface which, in principle, is different and has some advantages over the more common approach of numerical modeling of flow and transport equations. The five objectives were (i) Numerically develop a database for the prediction of water and solute distribution for irrigation; (ii) Develop predictive models using ANN; (iii) Develop an experimental (laboratory) database of water distribution with time; within a transparent flow cell by high resolution CCD video camera; (iv) Conduct field studies to provide basic data for developing and testing the ANN; and (v) Investigate the inclusion of water quality [salinity and organic matter (OM)] in an ANN model used for predicting infiltration and subsurface water distribution. A major accomplishment was the successful use of Moment Analysis (MA) to characterize “plumes of water” applied by various types of irrigation (including drip and gravity sources). The general idea is to describe the subsurface water patterns statistically in terms of only a few (often 3) parameters which can then be predicted by the ANN. It was shown that ellipses (in two dimensions) or ellipsoids (in three dimensions) can be depicted about the center of the plume. Any fraction of water added can be related to a ‘‘probability’’ curve relating the size of the ellipse (or ellipsoid) that contains that amount of water. The initial test of an ANN to predict the moments (and hence the water plume) was with numerically generated data for infiltration from surface and subsurface drip line and point sources in three contrasting soils. The underlying dataset consisted of 1,684,500 vectors (5 soils×5 discharge rates×3 initial conditions×1,123 nodes×20 print times) where each vector had eleven elements consisting of initial water content, hydraulic properties of the soil, flow rate, time and space coordinates. The output is an estimate of subsurface water distribution for essentially any soil property, initial condition or flow rate from a drip source. Following the formal development of the ANN, we have prepared a “user-friendly” version in a spreadsheet environment (in “Excel”). The input data are selected from appropriate values and the output is instantaneous resulting in a picture of the resulting water plume. The MA has also proven valuable, on its own merit, in the description of the flow in soil under laboratory conditions for both wettable and repellant soils. This includes non-Darcian flow examples and redistribution and well as infiltration. Field experiments were conducted in different agricultural fields and various water qualities in Israel. The obtained results will be the basis for the further ANN models development. Regions of high repellence were identified primarily under the canopy of various orchard crops, including citrus and persimmons. Also, increasing OM in the applied water lead to greater repellency. Major scientific implications are that the ANN offers an alternative to conventional flow and transport modeling and that MA is a powerful technique for describing the subsurface water distributions for normal (wettable) and repellant soil. Implications of the field measurements point to the special role of OM in affecting wettability, both from the irrigation water and from soil accumulation below canopies. Implications for agriculture are that a modified approach for drip system design should be adopted for open area crops and orchards, and taking into account the OM components both in the soil and in the applied waters.
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