Applied Computational Intelligence in Engineering and Information Technology

2012 ◽  
Keyword(s):  
Information Technology ◽  
Computational Intelligence

scholarly journals Quantum Fast Algorithm Computational Intelligence PT I SW HW Smart Toolkit

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Sergey Victorovich Ulyanov
Keyword(s):  
Information Technology ◽  
Soft Computing ◽  
Computational Intelligence ◽  
Fast Algorithm ◽  
Design Method ◽  
Quantum Algorithm ◽  
Circuit Implementation ◽  
Main Attention ◽  
New Approach ◽  
General Time

A new approach to a circuit implementation design of quantum algorithm gates for quantum massive parallel fast computing realization is presented. The main attention is focused on the development of design method of fast quantum algorithm operators as superposition, entanglement and interference which are in general time-consuming operations due to the number of products that have to be performed. SW & HW support sophisticated toolkit of supercomputing accelerator of quantum algorithm simulation is described. As example, the method for performing Grover’s interference without product operations introduced. The background of developed information technology is the "Quantum / Soft Computing Optimizer" (QSCOptKBTM) software based on soft and quantum computational intelligence toolkit. 

Computational Intelligence for Information Technology Project Management

2012 ◽  
pp. 1601-1624
Author(s):  
Robert J. Hammell ◽  
Julie Hoksbergen ◽  
James Wood ◽  
Mark Christensen
Keyword(s):  
Information Technology ◽  
Project Management ◽  
Computational Intelligence ◽  
Intelligent Systems ◽  
Project Managers ◽  
Success Rates ◽  
It Projects ◽  
It Project ◽  
Information Technology Project ◽  
Information Technology Project Management

With the growing complexity of information technology (IT) projects, the management of these projects is proving to be a daunting task. The magnitude of this problem is underscored by the assertion that approximately 70% of IT projects fail to meet their objectives (Lewis, 2007). Computational intelligence (CI) is an area of research focused on developing intelligent systems to help with complex problems. Specifically, CI seeks to integrate techniques and methodologies to assist in problem domains in which information, data and perhaps even the problem itself are vague, approximate, and uncertain. It would seem that research aimed at leveraging the power of CI against IT project management problems is critical if IT project success rates are to be improved. This work examines the core CI technologies – fuzzy logic, neural networks, and genetic algorithms – and looks at current and potential future applications of these techniques to assist IT project managers.

Computational Intelligence in the Financial Functions of Industrial Firms

2011 ◽  
pp. 2080-2098
Author(s):  
Petros Theodorou ◽  
Dimitrios Karyampas
Keyword(s):  
Information Technology ◽  
Production Planning ◽  
Computational Intelligence ◽  
Strategic Alignment ◽  
Production Operation ◽  
Industrial Firms ◽  
Planning And Control ◽  
Investment Appraisal ◽  
Operational Level ◽  
Computer Aided

Information technology has been proved to be a strategic weapon in the business armory for the creation and sustention of competitive advantage, especially, when it is aligned with the needs of the internal and external environment. Solutions are provided from the operational level up to strategic planning and are capable to support every choice in the strategy portfolio, from cost to quality and flexibility. IT systems in the manufacturing and operational level were analyzed extensively in literature: ERP systems, computer aided design/ computer aided manufacturing (CAD/CAM), and so forth. According to Wong, Bo, Bodnovich, and Selvi (1997), 53.5% of the reviewed literature in artificial intelligence refers to applications in production and operations management. Nevertheless, the second most important area for advanced IT applications is that of finance (25.4%). This research will be focused on the common set of the two previously mentioned areas: production management and the necessary financial tools. Production and operation management requires specific financial tools in order to accomplish the functions of production planning, costing, investment appraisal, and so forth. Computational intelligence in those financial functions is mostly needed for the production operation department and for the production operation strategy. Specifically, the weight will be put on information technology automation of financial functions adopted by production departments: forecasting production needs, production planning and control, profit volume analysis, cost analysis, investment appraisal analysis, and so forth. An attempt will be made to classify the various quantitative and qualitative techniques in relation to various financial aspects. Specifically, advances of neural networks, expert systems, advanced statistical analysis and operational research methods, and various hybrid techniques will be presented in relation to financial models applied in production. Financial applications will be analyzed according to their modules and their outputs in a strategic alignment concept. Finally, a strategic alignment model will be derived for the adoption of financialapplications in businesses.

Computational Intelligence for Information Technology Project Management

2010 ◽  
pp. 80-104 ◽  
Author(s):  
Robert J. Hammell ◽  
Julie Hoksbergen ◽  
James Wood ◽  
Mark Christensen
Keyword(s):  
Information Technology ◽  
Project Management ◽  
Computational Intelligence ◽  
Intelligent Systems ◽  
Project Managers ◽  
Success Rates ◽  
It Projects ◽  
It Project ◽  
Information Technology Project ◽  
Information Technology Project Management

With the growing complexity of information technology (IT) projects, the management of these projects is proving to be a daunting task. The magnitude of this problem is underscored by the assertion that approximately 70% of IT projects fail to meet their objectives (Lewis, 2007). Computational intelligence (CI) is an area of research focused on developing intelligent systems to help with complex problems. Specifically, CI seeks to integrate techniques and methodologies to assist in problem domains in which information, data and perhaps even the problem itself are vague, approximate, and uncertain. It would seem that research aimed at leveraging the power of CI against IT project management problems is critical if IT project success rates are to be improved. This work examines the core CI technologies – fuzzy logic, neural networks, and genetic algorithms – and looks at current and potential future applications of these techniques to assist IT project managers.

scholarly journals Internet of things as a solution for production and disaster activities in the province of Los Ríos

2018 ◽  
Vol 3 (CITT2017) ◽  
pp. 32-36
Author(s):  
Ana Fernández Torres ◽  
Jose Sandoya Villafuerte ◽  
Narcisa Crespo Torres ◽  
Yanina Marin Castillo
Keyword(s):  
Information Technology ◽  
Computational Intelligence ◽  
Teaching And Learning ◽  
Teaching Practice ◽  
Teaching Strategy ◽  
Social Significance ◽  
Technology Students ◽  
The Subject ◽  
Information Technology Students ◽  
Contextualized Learning

Teaching strategy presented aims to provide the contextualized learning computational intelligence in correspondence with the needs of the information technology students. This proposal is the output of a theoretical model that structure the process of teaching and learning of computational intelligence, from the dialectical relations between its components and it is manifested as a set of actions structured in three stages, defining their respective goals to transform the work, being done in the traditional way, towards new demands of renewal in the continuous improvement that is required, in correspondence with the needs that the learning of mathematical content has for the College student, social significance, and practical value. Assumes the contextualization as a contextual approach to the teaching of computational intelligence. The application of the teaching strategy in teaching practice confirmed its relevance, feasibility, and effectiveness through the use of empirical methods: evaluation by expert criteria, consultation with users and the pedagogical experiment in its pre-experiment variant, demonstrating favor the contextualized learning of the subject computational intelligence in the information technology students.

scholarly journals Research on Precision Cultivation of Digital Multimedia Crop Based on Predictive Computational Intelligence Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yuke Lin ◽  
Ying Zhang
Keyword(s):  
Information Technology ◽  
Dynamic Simulation ◽  
Computational Intelligence ◽  
Positive Role ◽  
Crop Cultivation ◽  
System Science ◽  
Agricultural Industry ◽  
Design Information ◽  
Digital Multimedia ◽  
Cultivation Technology

With the intersection and integration of modern crop cultivation and emerging disciplines, crop cultivation management is moving from traditional modeling and standardization to quantitative and intelligent direction. Crop precision cultivation technology is to apply system science and information technology to crop cultivation and digitally design information perception of the objects and processes involved in crop cultivation, dynamic simulation, so as to realize the quantification and accuracy of crop cultivation management. With the integration and intersection of modern digital multimedia crop cultivation and emerging disciplines, digital multimedia crop cultivation tends to gradually implement the quantitative and intelligent development, replacing the traditional scale and standardization. The technology of digital multimedia crop cultivation is to use science and information technology in digital multimedia crops to achieve the quantitative and precise characteristics of digital multimedia crop cultivation. The advancement of digital multimedia crop cultivation technology has greatly improved the management and benefits of the entire agricultural industry and has played a positive role in the development of agricultural information and modernity.

Computational Intelligence in the Financial Functions of Industrial Firms

2011 ◽  
pp. 44-62
Author(s):  
Petros Theodorou ◽  
Dimitrios Karyampas
Keyword(s):  
Information Technology ◽  
Production Planning ◽  
Computational Intelligence ◽  
Strategic Alignment ◽  
Production Operation ◽  
Industrial Firms ◽  
Financial Applications ◽  
Investment Appraisal ◽  
Operational Level ◽  
Computer Aided

Information technology has been proved to be a strategic weapon in the business armory for the creation and sustention of competitive advantage, especially, when it is aligned with the needs of the internal and external environment. Solutions are provided from the operational level up to strategic planning and are capable to support every choice in the strategy portfolio, from cost to quality and flexibility. IT systems in the manufacturing and operational level were analyzed extensively in literature: ERP systems, computer aided design/computer aided manufacturing (CAD/CAM), and so forth. According to Wong, Bo, Bodnovich, and Selvi (1997), 53.5% of the reviewed literature in artificial intelligence refers to applications in production and operations management. Nevertheless, the second most important area for advanced IT applications is that of finance (25.4%). This research will be focused on the common set of the two previously mentioned areas: production management and the necessary financial tools. Production and operation management requires specific financial tools in order to accomplish the functions of production planning, costing, investment appraisal, and so forth. Computational intelligence in those financial functions is mostly needed for the production operation department and for the production operation strategy. Specifically, the weight will be put on information technology automation of financial functions adopted by production departments: forecasting production needs, production planning and control, profit volume analysis, cost analysis, investment appraisal analysis, and so forth. An attempt will be made to classify the various quantitative and qualitative techniques in relation to various financial aspects. Specifically, advances of neural networks, expert systems, advanced statistical analysis and operational research methods, and various hybrid techniques will be presented in relation to financial models applied in production. Financial applications will be analyzed according to their modules and their outputs in a strategic alignment concept. Finally, a strategic alignment model will be derived for the adoption of financial applications in businesses.

Business: The Electronic Health Record: Front Line Experience

2011 ◽  
Vol 21 (1) ◽  
pp. 18-22
Author(s):  
Rosemary Griffin
Keyword(s):  
Health Care ◽  
Information Technology ◽  
Electronic Health Record ◽  
Financial Incentives ◽  
Best Practice ◽  
Health Care Systems ◽  
The United States ◽  
Health Record ◽  
Health Trends ◽  
Electronic Health

National legislation is in place to facilitate reform of the United States health care industry. The Health Care Information Technology and Clinical Health Act (HITECH) offers financial incentives to hospitals, physicians, and individual providers to establish an electronic health record that ultimately will link with the health information technology of other health care systems and providers. The information collected will facilitate patient safety, promote best practice, and track health trends such as smoking and childhood obesity.

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