Data Science Techniques in Knowledge-Intensive Business Processes

2020 ◽  
Vol 1 (1) ◽  
pp. 52-67
Author(s):  
Matthias Lederer ◽  
Joanna Riedl
Keyword(s):  
Fuzzy Logic ◽  
Business Intelligence ◽  
Data Science ◽  
Business Processes ◽  
Due Diligence ◽  
Fuzzy Logic Systems ◽  
Investment Bank ◽  
Front Office ◽  
Management Techniques ◽  
Knowledge Intensive

The processes of an investment bank are considered to be particularly knowledge-intensive, because analysts need to extract or generate relevant knowledge from a variety of data. With increasing digitization, modern data science and business intelligence techniques are available to support or partially automate these activities. This study presents concrete use cases for front office processes of an investment bank as how knowledge management techniques can be used. For example, the article describes how expert systems can be used in the due diligence review or how fuzzy logic systems help in deciding whether to buy or sell securities. The article is based on 1079 texts (e.g. documented cases and articles) and serves researchers as well as practitioners as an application overview of data science techniques in the example area of knowledge-intensive banking processes.

scholarly journals Digital Transformation of Forest Services in Finland—A Case Study for Improving Business Processes

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 781
Author(s):  
Ville Kankaanhuhta ◽  
Tuula Packalen ◽  
Kari Väätäinen
Keyword(s):  
Business Processes ◽  
Innovation Process ◽  
Single Type ◽  
Stand Management ◽  
Young Stand ◽  
Commercial Viability ◽  
Soil Preparation ◽  
Knowledge Intensive ◽  
Agile Software

This case study introduces an innovation and development concept for agile software tools for the improvement of the productivity and customer experience of forest services. This need was recognized in the context of the opening of forest data and the development of service platforms for a forest-based bioeconomy in Finland. The forest services that were studied covered a continuum from a single type of work, e.g., soil preparation and young stand management through timber procurement, to comprehensive forest property management services. The study concentrated on the needs of micro-, small, and medium-sized enterprises (SMEs), which provide either retail- or business to business (B2B) services as sub-contractors. In addition, the challenges and bottlenecks in service processes detected by other stakeholders were considered. The prevailing service processes were conceptually modelled in order to search for opportunities for improvements in business and ecosystem services, i.e., agile software concepts. For example, we examined whether it would be possible to create opportunities for flexible operational models for precision, resilience, and protection of valuable microsites in forests. These software concepts were developed and evaluated in co-operation with the stakeholders in a co-creative workshop. The technological feasibility and commercial viability of the concepts, as well as the desirability for the customer were considered. The results of this business development process—i.e., agile software concepts and their anticipated benefits—were provided for further evaluation. In addition to the practical implications of this kind of innovation process tested, the potential of these kinds of agile tools for the further development of knowledge-intensive service processes was further discussed.

Design of back propagation optimized Nagar-Bardini structure-based interval type-2 fuzzy logic systems for fuzzy identification

2021 ◽  
pp. 014233122110066
Author(s):  
Yang Chen ◽  
Jiaxiu Yang
Keyword(s):  
Fuzzy Logic ◽  
Back Propagation ◽  
Membership Functions ◽  
Identification Problems ◽  
Fuzzy Logic Systems ◽  
Fuzzy Identification ◽  
Logic Systems ◽  
Academic Topic ◽  
Interval Type

In recent years, fuzzy identification based on system identification theory has become a hot academic topic. Interval type-2 fuzzy logic systems (IT2 FLSs) have become a rising technology. This paper designs a type of Nagar-Bardini (NB) structure-based singleton IT2 FLSs for fuzzy identification problems. The antecedents of primary membership functions of IT2 FLSs are chosen as Gaussian type-2 primary membership functions with uncertain standard deviations. Then, the back propagation algorithms are used to tune the parameters of IT2 FLSs according to the chain rule of derivation. Compared with the type-1 fuzzy logic systems, simulation studies show that the proposed IT2 FLSs can obtain better abilities of generalization for fuzzy identification problems.

Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

2011 ◽  
Vol 62 (2) ◽  
pp. 147-163 ◽  
Author(s):  
Sunday Olusanya Olatunji ◽  
Ali Selamat ◽  
Abdulazeez Abdulraheem
Keyword(s):  
Fuzzy Logic ◽  
Carbonate Reservoir ◽  
Fuzzy Logic Systems ◽  
Logic Systems
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