View, Level and Fragment: Commonalities in “Architecture 101” and Software Modelling

2012 ◽  
pp. 63-71
Author(s):  
K. O. Chow
Keyword(s):  
Software Modelling

scholarly journals The study of the movement of a piece on the camera crushing in network type bases as applied to the workflow of the FCC

2020 ◽  
Vol 177 ◽  
pp. 03011
Author(s):  
Yuliya Lagunova ◽  
Victor Shestakov ◽  
Nazira Ibrayeva
Keyword(s):  
Raw Materials ◽  
Main Aspect ◽  
Working Process ◽  
Work Process ◽  
Solid Materials ◽  
Subsequent Decrease ◽  
Cone Crusher ◽  
Software Modelling ◽  
Basic Characteristics ◽  
Network Type

The paper considers a software-modelling structure for solving the problem of crushing of solid materials, mountain mineral raw materials of different strength and composition. The task is to study the movement of a piece along the crushing chamber of a cone crusher, the stages of destruction of pieces are considered. Setting the main parameters of the FCC, the working process of the crusher and the parameters of the destruction of pieces in the crushing chamber. The study of the basic characteristics of the movement process, the interaction and destruction of pieces is the main aspect of the work process. More precisely, the issues were examined, on the basis of which the dependencies were compiled, which are used in the algorithm of the model of the working process of FCC at the beginning of the cycle of the mode of movement. One of the processes considered in the article is squeezing a piece between the armors with a subsequent decrease in the distance between the armors.

An Applied Mathematical Model for Business Transformation and Enterprise Architecture

2020 ◽  
pp. 433-463
Keyword(s):  
Research And Development ◽  
Research Method ◽  
Enterprise Architecture ◽  
Financial Analysis ◽  
Development Project ◽  
Research Management ◽  
Business Transformation ◽  
Research Concept ◽  
Software Modelling ◽  
Business Engineering

This chapter presents the resources management system's research and development project (RMSRDP) that explains in detail the application of the research concept where the enterprise research management (ERM)-based transformation projects are carried on to optimize enterprise resources in transformed end enterprises, the result of an innovative research and development on 1) business resources-oriented case studies, 2) ERM, 3) business transformations, 4) applied mathematical models, 5) software modelling, 6) business engineering, 7) financial analysis, 8) decision-making systems and CSFs, 9) artificial intelligence (AI), and 10) enterprise architecture. The RMSRDP is based on an authentic and proprietary research method and framework that are supported by an underlining mainly qualitative holistic reasoning model module.

An Applied Mathematical Model for Business Transformation and Enterprise Architecture

2020 ◽  
pp. 377-406
Keyword(s):  
Research Method ◽  
Enterprise Architecture ◽  
Financial Analysis ◽  
Applied Mathematics ◽  
Project Teams ◽  
Resources Management ◽  
Business Transformation ◽  
Software Modelling ◽  
Business Engineering ◽  
Language Environment

This chapter presents the resources management implementation concept (RMIC)-based transformation projects to optimize resources creation/management in a transformed enterprise system, the result of research and development on 1) business resources case studies, 2) resources management, 3) business transformations, 4) applied mathematics/models, 5) software modelling, 6) business engineering, 7) financial analysis, 8) decision-making systems, 9) artificial intelligence (AI), and 10) enterprise architecture. The RMIC is based on an authentic and proprietary research method that is supported by an underlying mainly qualitative holistic reasoning module, which is an AI/empirical process that uses a natural language environment that can be easily adapted by the project teams.

An Applied Mathematical Model for Business Transformation and Enterprise Architecture

2020 ◽  
pp. 172-210
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Research Method ◽  
Enterprise Architecture ◽  
Financial Analysis ◽  
Applied Mathematics ◽  
Decision Making System ◽  
Information And Communication ◽  
Software Modelling ◽  
Business Engineering

This chapter proposes a cross-business domain holistic mathematical model (HMM) that is the result of a lifetime of research on business transformations, applied mathematics, software modelling, business engineering, financial analysis, and global enterprise architecture. This research is based on an authentic and proprietary mixed research method that is supported by an underlining mainly qualitative holistic reasoning model module. The proposed HMM formalism attempts to mimic some functions of the human brain, which uses empirical processes that are mainly based on the beam-search, like heuristic decision-making process. The HMM can be used to implement a decision-making system or an expert system that can integrate the enterprise's business, information, and communication technology environments.

scholarly journals The use of machine learning methods in the diagnosis of diseases of crops

2020 ◽  
Vol 176 ◽  
pp. 04011
Author(s):  
Sergey Korchagin ◽  
Denis Serdechny ◽  
Roman Kim ◽  
Denis Terin ◽  
Mihail Bey
Keyword(s):  
Machine Learning ◽  
Plant Diseases ◽  
Agricultural Crops ◽  
Learning Methods ◽  
Agricultural Enterprises ◽  
Machine Learning Methods ◽  
Diagnosis And Prognosis ◽  
Software Modelling ◽  
The Cost ◽  
Recurrent Type

The approach to solving the problems of diagnosis and prognosis of diseases of agricultural crops using machine learning methods is described. To solve the problem of forecasting diseases of agricultural crops, it is proposed to use a genetic algorithm in the work. The analysis of the effectiveness of the proposed method is carried out depending on the convergence rate of such parameters as the mutation coefficient and population size. To solve the problem of diagnostics of agricultural crops, it is proposed to use a recurrent type of neural network. A software modelling complex has been developed that allows solving the problems of plant diseases diagnostics and making forecasts. The results obtained can reduce the costs of agricultural enterprises by reducing the cost of diagnosing agricultural diseases.

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