scholarly journals Managing business processes using soft computing techniques – a literature review

2017 ◽  
Vol 23 (1) ◽  
pp. 63 ◽  
Author(s):  
Nikola D. Vojtek
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Process Management ◽  
Business Processes ◽  
External Factors ◽  
Business Operations ◽  
Soft Computing Techniques ◽  
Internal And External Factors ◽  
And Behavior

Non-ideal and turbulent environment is affecting the business operations of today's companies. The influence and behavior of external factors is not possible or very difficult to predict, but necessary to consider in the decision making process at all organizational levels. Development of computer technologies allowed companies processing large amounts of data in order to make decisions which take into account both internal and external factors. Due to their tolerance of imprecision and uncertainty, Soft computing techniques (SCT) are increasingly used in solving those problems. They are characterized by the ability to adapt quickly to the changes in the environment, stability when processing large amounts of inaccurate data and real time responsiveness. The basic and most commonly used Soft Computing techniques are Fuzzy logic (FL) and neural networks (NN). This paper gives a review of 78 papers referring to the development of theory and practical application of soft computing techniques in business process management. Papers were selected based on the journals impact factor and year of publication (with the focus on recent papers). Approximately, equal number of both Fuzzy logic and Neural Network techniques was tried to be captured. Although this review is not final, it can be considered as a valid guide to explore the opportunities and possibilities which fuzzy logic and neural networks offer process owners in managing their business processes. In conclusion of this paper, fields for further research have been identified.

Study of Feature Apprehension Using Soft Computing Approaches

2018 ◽  
pp. 170-190
Author(s):  
Deepika Dubey ◽  
Deepika Singh Kushwah ◽  
Deepanshu Dubey
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Region Of Interest ◽  
Image Database ◽  
The Other ◽  
Soft Computing Techniques ◽  
Similar Images ◽  
The One

An image may be mist full for the one or may be nostalgic for the other. But for a researcher, each image is distinguished on the basis of its low-level features like color, shape, size. Other features like edges, corner/interesting points, blobs/region of interest, ridges, etc. can also be used for computation purpose. Using these features distinctions, an image can be processed for the purpose of enhancing the images having same features, matching, and shortlisting of similar images from a random available image database. This could be done using soft computing techniques like neural networks, fuzzy logic, and evolutionary computation methods. Neural networks can participate effectively in image processing in several ways.

Menumbuhkan Jiwa, Perilaku dan Nilai Kewirausahaan Dalam Meningkatkan Kemandirian Bisnis

MBIA ◽  
2019 ◽  
Vol 17 (2) ◽  
pp. 23-32
Author(s):  
Deddy Hendarwan
Keyword(s):  
Small Businesses ◽  
Positive Influence ◽  
External Factors ◽  
Entrepreneurial Behavior ◽  
Environmental Pressures ◽  
Entrepreneurial Spirit ◽  
Internal And External Factors ◽  
And Behavior ◽  
Ownership Rights ◽  
Attitudes And Behavior

Attitudes and behaviors are the unity of a person's character which is formed by habit everyday. Entrepreneurial behavior is influenced by internal and external factors. These factors are ownership rights (property right, PR), abilities / competencies (competency / ability,), and incentives while external factors include the environment thus Attitudes and behavior can be changed by oneself and / or there are environmental pressures / influences. there is an influence from within themselves and from outside the environment to associate then grow indi attitudes and specific behaviors. It is necessary to anticipate small businesses’ difficulties by conducting an empirical study  on  the  entrepreneurial  spirit,  entrepreneurial  values,  and  assessment  of entrepreneurial behavior that may affect the realization of independence efforts. This study  aims to  analyze the  influence of  entrepreneurial spirit  and entrepreneurial values on entrepreneurial behavior to create business independence. The findings show that the entrepreneurial spirit has a direct positive influence on entrepreneurial behavior and positive indirect effect on the business independence.

Artificial Intelligence in Business Processes

2022 ◽  
pp. 205-230
Author(s):  
S. Asif Basit
Keyword(s):  
Neural Networks ◽  
Process Management ◽  
Business Processes ◽  
Control Process ◽  
Shop Floor ◽  
Business Environments ◽  
Novel Approach ◽  
Governing Factor ◽  
Artificial Neurons ◽  
Process Interaction

The aim of this chapter is to establish that the principles used by neural networks can be applied to business process management. The similarity between artificial neurons and business processes, and hence between neural networks and process landscapes, will be demonstrated. This novel approach leads to an emphasis on process interactions and their effect on actions as a major governing factor in controlling process outputs. Stigmergic interaction in biological systems is explored in the context of business processes, and its potential to understand process interaction is investigated. In order to verify the use of stigmergy in business environments, a pilot study is described in which shop floor business processes in a retailing environment are observed and described using a stigmergic framework. Establishing the viability of using stigmergic interaction to control process actions and outputs is the first step towards designing neural process networks.

Soft case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 267-269 ◽  
Author(s):  
WILLIAM CHEETHAM ◽  
SIMON SHIU ◽  
ROSINA O. WEBER
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Network Theory ◽  
Probabilistic Reasoning ◽  
Case Based Reasoning ◽  
Case Representation ◽  
Soft Computing Techniques ◽  
Neural Network Theory ◽  
Case Based

The aim of this commentary is to discuss the contribution of soft computing—a consortium of fuzzy logic, neural network theory, evolutionary computing, and probabilistic reasoning—to the development of case-based reasoning (CBR) systems. We will describe how soft computing has been used in case representation, retrieval, adaptation, reuse, and case-base maintenance, and then present a brief summary of six CBR applications that use soft computing techniques.

scholarly journals Towards Robustness in Neural Network Based Fault Diagnosis

2008 ◽  
Vol 18 (4) ◽  
pp. 443-454 ◽  
Author(s):  
Krzysztof Patan ◽  
Marcin Witczak ◽  
Józef Korbicz
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fault Diagnosis ◽  
Soft Computing ◽  
Analytical Techniques ◽  
Industrial Applications ◽  
Nonlinear Behaviour ◽  
Design Problems ◽  
Modelling Uncertainty ◽  
Soft Computing Techniques

Towards Robustness in Neural Network Based Fault DiagnosisChallenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being diagnosed as well as the robustness of a fault diagnosis scheme with respect to modelling uncertainty, two different neural network based schemes are described and carefully discussed. The final part of the paper presents an illustrative example regarding the modelling and fault diagnosis of a DC motor, which shows the performance of the proposed strategy.

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