Complex Fuzzy Logic Reasoning-Based Methodologies for Quantitative Software Requirements Specifications

Author(s):  
Dan E. Tamir ◽  
Carl J. Mueller ◽  
Abraham Kandel
2020 ◽  
Vol 9 (2) ◽  
pp. 215
Author(s):  
Dwi Januarita AK

The rapid development of technology makes this technology have an impact on many fields, one of which is the business world. The number of businesses that have emerged both small and large businesses that have an impact on competition between these businesses. Today, business in the culinary field is getting tougher. The culinary business sector of restaurants is increasingly popping up in this age. We need to overcome the competition in the emerging restaurant business. By using the stages of making software requirements specifications based on ISO / IEC / IEEE 29148-2018, this restaurant business will have an international standard information system. The result of this method is a software requirements specification document (SKPL) as a reference document for all activities carried out during the development of this information system.


Author(s):  
Norman F. Schneidewind

In order to continue to make progress in software measurement, as it pertains to reliability and maintainability, there must be a shift in emphasis from design and code metrics to metrics that characterize the risk of making requirements changes. By doing so, the quality of delivered software can be improved because defects related to problems in requirements specifications will be identified early in the life cycle. An approach is described for identifying requirements change risk factors as predictors of reliability and maintainability problems. This approach can be generalized to other applications with numerical results that would vary according to application. An example is provided that consists of 24 space shuttle change requests, 19 risk factors, and the associated failures and software metrics.


2022 ◽  
Vol 355 ◽  
pp. 03007
Author(s):  
Xiaohong Qiu ◽  
Jiali Chen

Stall warning of axial compressor is very challenging and the existing warning margin is not enough. A algorithm based on BP neural network fusion fuzzy logic is proposed. Firstly, BP neural network is used for training recognition, next the identification results are fused with fuzzy logic reasoning to form the result judgment of time sequence, finally the stall early warning of axial compressor is realized. The simulation results of the experimental data show that the stall data at all speeds are at least 0.1s in advance of the early warning. Compared with other methods, this method has a better surge early warning margin performance and engineering practicability.


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