Soft Computing Seminar and PPT with pdf report
Soft Computing Seminar and PPT with pdf report: As we know, there are more intricate concepts are coming in the field of biology, medicines and in management science. All these intricate fields persisted untraceable to conventional mathematics and analytical methods. Here enters the concept of soft computing, soft computing deals with uncertainty, biased truth and quite exact to achieve traceability, robustness and fewer cost solutions.
Soft Computing Seminar and PPT with PDF Report
Soft computing not like the conventional computing i.e. hard computing and the idol for the soft computing is the human mind. It has the guiding principles like from the development of the tolerance for uncertainty, biased truth and up to the affordable solutions. The basic ideas of the present soft computing have the relations with the past like Zaden’s paper in 1965 on fuzzy sets, with the complex systems and decision process in 1973 and still, there are many others.
At this point of view, the principle components of soft computing (SC) are fuzzy Logic (FC), neutral computing (NC) and evolutionary computation (EC), machine learning (ML) and probabilistic reasoning (PR). The soft computing is not the collection of things but it is a partnership in which each partner contributes the different methods for the issues of their respective domain. Overall the soft computing is believed to be a constituent for the coming field of conceptual intelligence.
The importance of soft computing:
The perfection of fuzzy logic (FL), neural computing (NC), genetic computation (GC) and probabilistic reasoning (PR) has a vital consequence; in many cases an issue can be sought out most perfectly by using fuzzy logic, neural computing, genetic computation and probabilistic reasoning together rather than using the one and only method. One example of the perfect combination is the neuro-fuzzy systems and such systems are developing as consumer systems ranging from air conditioners to the camcorders.
The neuro-fuzzy systems also play a vital role in the industries. The vital point to note is that in both consumer and industrial goods soft computing technology leads to the systems with good machine intelligence quotient i.e. MIQ. The suggestion of the soft computing to the students is that they should be trained not only in fuzzy logic, neural computing, genetic computation and probability reasoning but also in other methods although they are not so vital or important.
Presently, the Berkeley Initiative on Soft Computing group i.e. BISC have 600 students, employees of a private sector and non-private sector and also the individual people who have the interest in soft computing. This group has nearly 50 affiliated institutes and they are going to enhance in the future too. At Berkeley, BISC furnishes a supporting atmosphere for students and visitors who have the keen interest in soft computing.
Hard computing Vs soft computing:
- Hard computing is nothing but the conventional computing; it needs an accurate stated analytical model and sometimes needs a lot of calculation time. The soft computing deals with uncertainty, biased truth and quite exact to achieve traceability, robustness and fewer cost solutions.
- The hard computing depends on binary logic, crisp systems, and collection of programs. Coming to the soft computing it depends on fuzzy logic, neural computing, evolutionary computation, and probability reasoning.
- Hard computing has the feature of being accurate and the soft computing is near to the accuracy.
- The hard computing needs the list of instructions to be written, the soft computing can have its own collection of instructions.
- Hard computing and soft computing are deterministic and stochastic respectively.
- Hard computing needs accurate input information, soft computing can even deal with noisy information.
- Hard computing follows a sequential process and soft computing permits parallel calculations.
- Hard computing generates accurate answers and soft computing furnishes approximate solutions.
Tools of soft computing:
Some of the tools that are used in soft computing and they are as follows:
- Fuzzy logic methods
- Neural networks
- Genetic algorithm
- Machine learning
- Probabilistic reasoning
All these tools work in a combined way and solve many complex real world issues, the other techniques are not so good in solving these kinds of issues. The aim of this is to furnish the software for soft computing with unique attention to fuzzy system software.
Future scope of soft computing:
Overall the successful applications of soft computing have proved that in the coming era the avail of soft computing will be enhanced. The fast growth of Berkeley Initiative on Soft Computing group suggests that the influence of soft computing will be enhanced in the coming generation. Soft computing will play a vital role in science and engineering and will have a wide range of applications too.
Content of the Seminar and pdf report for Soft computing
- What is Soft Computing?
- Soft Computing Tools
- Future of Soft Computing
- Hard Computing Vs Soft Computing
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