Q2. What are the future works mentioned in the paper "Development of soft computing and applications in agricultural and biological engineering" ?
Although no successful applications of hard and soft computing fusion in agricultural and biological engineering could be found thus far, the technique shows great potential for future research over the next decade.
Q3. What are the main applications of soft computing in agricultural and biological engineering?
In agricultural and biological engineering, researchers and engineers have developed methods for FL, ANNs, GAs, Bayesian Inference (BI), Decision Tree (DT), and SVMs to study soil and water regimes related to crop growth, analyze the operation of food processing, and support decision-making in precision farming.
Q4. What are the primary methods of significant utility in agriculture and biological engineering?
For research and development in agricultural and biological engineering, primary methods of significant utility include FL, ANNs, GAs, BI and DT.
Q5. What type of spectrometer was used to obtain scans of the plots?
In this study, an aircraft-mounted pushbroom imaging spectrometer was used to obtain scans of the plots in one blue, five green, five red, and thirteen infrared bands.
Q6. What are the main advantages of SVMs?
SVMs as a new set of supervised generalized linear classifiers, have been introduced to solve problems and have attracted greater interest recently in agricultural and biological engineering.
Q7. What are the main applications of ANNs?
In food science and engineering, soil and water relationships for crop management, and decision support for precision agriculture, more applications of ANNs may be expected.
Q8. What is the main reason why SVMs are becoming more popular?
With the advantages of SVMs over ANNs and the growing interests of SVMs, it can be expected that in the next decade SVMs will be more actively used in agricultural and biological engineering.
Q9. What is the function of the inference engine?
The inference engine analyzes user query and sends information requests to the knowledge base and matches them with the stored knowledge rules through fuzzy ‘If–Then’ rules or algorithms specific to the particular domain or discipline.
Q10. How many papers and reports are fusion of soft computing techniques?
The list indicates that the integration of FL and ANNs is probably the most common method of fusion in soft computing (thirteen out of twenty-nine collected papers and reports).
Q11. How many fuzzy rules were used to determine the ET?
To calculate the crop water stress index under different levels of solar radiation and vapor pressure deficit, 150 fuzzy rules were established to relate the system inputs and the output.
Q12. What is the useful method for predicting organic matter content in Saskatchewan?
Ingleby and Crowe (2001) developed feedforward ANN models with a reduced-memory Levenberg–Marquardt BP training algorithm for predicting organic matter content in Saskatchewan soils.
Q13. What is the future of soft computing in agricultural and biological engineering?
The future of the development and application of soft computing in agricultural and biological engineering is discussed, especially in the soil and water context for crop management and in decision support in precision agriculture.
Q14. How many peer reviewed papers were written on SVMs?
It is interesting to note that 20 reports and papers (13 peer reviewed) were written on SVMs from 2003 to present, 7 (2 peer reviewed) of which were published in 2008.
Q15. What were the characteristics of different fusion schemes?
Different fusion schemes were classified as 12 core categories and six supplementary categories, and the characteristic features of soft computing and hard computing constituents in practical fusion implementations were discussed as well.
Q16. What is the largest body of applications in agricultural and biological engineering?
ANNs have the largest body of applications in agricultural and biological engineering when compared with other soft computing techniques.