Learning Something Right from Models That Are Wrong: Epistemology of Simulation

Tolk, Andreas

doi:10.1007/978-3-319-15096-3_5

Cited by 24 publications

(12 citation statements)

References 25 publications

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“…Erosion modelling is used in order to achieve a better understanding of erosion processes, provided that experimental conditions from which directly measured outcomes could be derived, are either impossible or impractical to create ( Tolk, 2015 ). The importance and achievements of erosion modelling (either for soil loss, sediment yield, or both) have been argued by a plethora of research works; see the review of Merritt et al (2003) .…”

Section: Introductionmentioning

confidence: 99%

The G2 erosion model: An algorithm for month-time step assessments

Karydas¹,

Panagos

2018

Environmental Research

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A detailed description of the G2 erosion model is presented, in order to support potential users. G2 is a complete, quantitative algorithm for mapping soil loss and sediment yield rates on month-time intervals. G2 has been designed to run in a GIS environment, taking input from geodatabases available by European or other international institutions. G2 adopts fundamental equations from the Revised Universal Soil Loss Equation (RUSLE) and the Erosion Potential Method (EPM), especially for rainfall erosivity, soil erodibility, and sediment delivery ratio. However, it has developed its own equations and matrices for the vegetation cover and management factor and the effect of landscape alterations on erosion. Provision of month-time step assessments is expected to improve understanding of erosion processes, especially in relation to land uses and climate change. In parallel, G2 has full potential to decision-making support with standardised maps on a regular basis. Geospatial layers of rainfall erosivity, soil erodibility, and terrain influence, recently developed by the Joint Research Centre (JRC) on a European or global scale, will further facilitate applications of G2.

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Section: Introductionmentioning

confidence: 99%

The G2 erosion model: An algorithm for month-time step assessments

Karydas¹,

Panagos

2018

Environmental Research

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“…Routes along the rocks for novice tourists have been created and presented graphically using the modeling of routes. It is the modeling as a method of routes visualization (Tolk, 2015) allows them to use the received developments as a ready-made tourist offer, if they have the relevant equipment, as well as a specialist with the required competence in the field of active types of tourism and climbing. Thus, this study is the implementation of a step-by-step methodology, including both general scientific methods (analysis, synthesis, scientific search) and practical methods (field research, modeling, experiment), and can be formed in several stages:…”

Section: Methodsmentioning

confidence: 99%

Promising Directions for the Development of Sports Tourism in the Almaty Region Using the Example of Rock Climbing

BATYRBEKOV¹,

Imangulova²,

Gubarenko³

et al. 2022

GTG

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The aim of the study was the process of studying the phenomenon of rock climbing development as one of the promising areas of sports tourism in the Almaty region of the Republic of Kazakhstan, which has a wide range of tourist resources systematically involved in various types of tourism. The research method was a large-scale, extended analysis of the tourist attractiveness of the region, and thus defined the most popular tourism destinations, as well as the persistent association of the Almaty region with mountain and foothill terrain, sports tourism and rock climbing. As a result of the research, the authors have formed a clear understanding of rock climbing as one of the promising areas for the development of sports tourism, which is currently becoming increasingly popular among both the local population and tourists of different ages. Sports tourism, rock climbing on natural and artificial (specially created) terrain, requires significant resource provision with respect to both the rock climbing sites, and professional personnel in the field of tourism who possess competencies in the field of sports tourism, ensuring the implementation of this tourist service. The results of the research presented in this article are based on the professional activities of the authors and allow them to have a qualitative impact on the process of training the sports tourism personnel, and contribute to the development of different-level routes for tourists wishing to engage in rock climbing, expand the involvement of tourists and contribute to the development of touristic attractiveness of the regions of the country.

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“…that is a significant drawback, which complicates the further use of such models. The development of model building theory [1][2][3][4][5][6] demonstrates the need to supplement a model also with other informational attributes that are necessary for its analysis, selection, and operation [9]. The literature demonstrates [24] that existing types of models are mainly reduced to a nonlinear algebraic equation, a system of nonlinear algebraic equations, nonlinear boundary-value problems, and a system of nonlinear differential equations [24,28].…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…It should be noted that for the assigned value of a model error magnitude, which is represented in implicit form (3), following its transformation to explicit form (6), the error takes the form of a vector and is calculated from (10), including using norm (2). Simultaneous application of operations of squaring and the specified integration in the assigned interval and extracting the square root leads to the formation of a magnitude of the mean integral square error:…”

Section: Constructing An Expression For the Express Computation Ofmentioning

confidence: 99%

“…It is generally known that studying an object, as well as structures and processes, implies forming their simplified representation in the form of a model [1]. Various forms of model representation in automated systems are reduced to elementary binary numerical display in code and the defined set of mathematical operations [2]. Despite the formal simplicity of such sets, their totality in most models of real-life processes [3] takes complex linear or non-linear mathematical forms [4].…”

Section: Introductionmentioning

confidence: 99%

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Forming a мetodology for transforming a model as the basis for expanding its informativeness

Trunov

2019

EEJET

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Поставлена та розв'язана задача побудови методологiї перетворення неявної форми моделi, що пiдвищує ефективнiсть замiни складних нелiнiйних форм математичних моделей зведенням їх до рекурентної послiдовностi у виглядi аналiтичних виразiв, якi допускають швидкi експрес обчислення. Запропоновано новi явнi форми моделей, що дозволяють застосовувати рекурентнi послiдовностi для представлення розв'язку задачi i формування виразу оцiнки похибки та iншої додаткової iнформацiї. У зв'язку з тим, що утворюючими для багатьох ознак є роз'язок та оцiнка похибки, аналiтичнiсть виразiв вiдкриває новi властивостi i можливостi. Грунтуючись на таких факторах як достовiрнiсть, точнiсть, глибина, суттєвiсть та повнота, адекватнiсть моделi представлено єдиним аналiтичним виразом, що дозволить у подальшому спрощувати процес порiвняння, за рахунок застосування кiлькiсних методiв. Представлення перетворень, вiдповiдно до яких встановлено зв'язок мiж похибкою двох послiдовних наближеннь та залежнiстю вiд номеру наближення, зумовлено необхiднiстю аналiзу динамiки збiжностi за номером наближення. Другим не менш важливим варiантом, що може характеризувати динамiку збiжностi, є зв'язок похибки першого наближення та довiльного. На пiдставi загального розвинення неявної форми моделi та теореми про середнє встановлено зв'язок мiж двома послiдоними похибками або нормами. Продемонстровано, що якщо похибка або норма похибки задана, то оцiнки першої та другої похiдних дозволять визначати граничний номер iтерацiї, починаючи з якої похибка менша за задану. Наведено приклад виводу оцiнки для загальної моделi величини максимально можливої похибки, граничного номеру iтерацiї, починаючи з якої похибка набуває значення менше за задане. Виведено також комплексну аналiтичну оцiнку адекватностi за єдиним виразом. Представлення iнформацiйних ознак у кiлькiснiй формi обумовлено новими можливостями, що буде утворено за рахунок отриманих iнструментiв для кiлькiсного аналiзу. Проведено чисельне моделювання та дослiджено характер динамiки нових iнформацiйних показникiв та ознак. Представленi данi для дев'яти iтерацiй демонструють ефективнiсть та повноту iнформацiї. для швидкого аналiзу i висновку. На пiдставi динамiки кiлькiсних ознак вiдносної похибки та нових, що пропонуються за результатами iмплементацiї методологiї перетворення моделi, показано, що вiдкриваються можливостi швидкого аналiзу i висновку. Продемонстровано, що введенi ознаки розширюють iнформацiйнiсть реалiзацiї методологiї для подальшого представлення нелiнiйної моделi у виглядi рекурентної послiдовностi Ключовi слова: нелiнiйна вектор-функцiя, рекурентна модель, iнформацiйнi ознаки, аналiтичнi вирази, оцiнка похибки, гранична iтерацiя, оцiнка адекватностi

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Learning Something Right from Models That Are Wrong: Epistemology of Simulation

Cited by 24 publications

References 25 publications

The G2 erosion model: An algorithm for month-time step assessments

The G2 erosion model: An algorithm for month-time step assessments

Promising Directions for the Development of Sports Tourism in the Almaty Region Using the Example of Rock Climbing

Forming a мetodology for transforming a model as the basis for expanding its informativeness

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