Many stock investors make investment decisions based on stock-price-related chip indicators. However, in addition to quantified data, financial news often has a nonnegligible impact on stock price. Nowadays, as new reviews are posted daily on social media, there may be value in using web opinions to improve the performance of stock price prediction. To this end, we use logistic regression to screen the chip indicators and establish a basic stock price prediction model. Then, we employ text mining technology to quantify the unstructured data of social media opinions on stock-related news into sentiment scores, which are found to correlate significantly with the change extent of the stock price. Based on the findings that the higher the sentiment scores, the lower the prediction accuracy of the logistic regression model, we propose an improved prediction approach that integrates sentiment scores into the logistic regression model. Our results show that the proposed model can improve the prediction accuracy for stock prices, and can thus provide a new reference for investment strategies for stock investors.
Purpose
This paper aims to propose an integrated bionic optimal design system to assist engineers in bionic design tasks. In this age of ecological awareness and sustainability, engineers are increasingly applying bionics to their product designs. A recent surge of research on bionics has presented new opportunities and challenges. To deal with these challenges, an integrated design system equipped with the capabilities of conducting biologically inspired design, solving technical contradictions, optimizing design parameters and verifying design effectiveness is required.
Design/methodology/approach
This study proposes a two-level analysis to help decision makers conduct multi-faceted observation and assessment on conceptual bionic design. The contradictions incurred when transferring biological principals to engineering design are solved using BioTRIZ, and the conceptual design is then created. This study conducts computer-aided engineering analysis, incorporating the Taguchi method and TOPSIS method, to obtain the optimal design of bionic products.
Findings
The proposed design process focuses on improving the product structure instead of changing the materials, and thus, the authors are able to put the goals of saving energy, environmental protection and sustainability into practice.
Practical implications
Through the design and analysis processes, the authors prove that their designed bionic-fan can effectively enhance operational efficiency and reduce the aerodynamic noise. The system can provide a practical tool for engineers intending to accomplish complete designs and verifications using bionics.
Originality/value
Most existing design methodologies that have attempted to combine biology with engineering design have fallen short in their level of thoroughness. This study proposes a complete bionic design system by integrating the processes of bionic-inspired design, optimization and verification.
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