Soft_Computing_Presentation for soft computing

Soft_Computing_Presentation for soft computing

• 1.
  Soft Computing Overview andApplications
• 2.
  Introduction to SoftComputing – From childhood, we are taught strict rules that always hold true. – In the real world, it's not always possible to find precise answers. – Natural systems tend to do things they believe are true rather than what is compulsorily true. – Real life is filled with uncertainty and imprecision.
• 3.
  Example of Uncertainty –A child asked to separate 1000 pieces of fruit may struggle with precision. – Real-life scenarios involve imprecision and approximations. – Uncertainty exists not only in natural systems but also in human-made systems.
• 4.
  Applications of SoftComputing – Soft computing is used in speaker recognition, handwriting recognition, face recognition, disease identification, etc. – Systems using soft computing handle uncertainties and imprecisions.
• 5.
  Soft Computing vsHard Computing – Hard computing deals with precise computation using strict rules. – Soft computing handles problems with imprecision and uncertainty. – Soft computing sacrifices some precision for solving complex, real- world problems.
• 6.
  Definitions of SoftComputing – Soft computing is an emerging approach to computing that parallels the human mind's ability to reason and learn in an environment of uncertainty and imprecision. - Prof. Lofti Zadeh – The guiding principle of soft computing is to exploit tolerance for imprecision and uncertainty to achieve tractability, robustness, and low solution cost. - Prof. Lofti Zadeh
• 7.
  Optimization Problems – Optimizationinvolves finding optimal values for parameters that minimize an objective (cost) function. – Soft computing techniques are well-suited for handling optimization problems.
• 8.
  Advantages of SoftComputing – Soft computing can solve problems that are too complex for traditional methods. – It offers robust and scalable solutions with little loss of precision.
• 9.
  Applications of SoftComputing – Biometrics, Bioinformatics, Biomedical Systems, Robotics, Vulnerability Analysis, Character Recognition, Data Mining, Music, Natural Language Processing, Multiobjective Optimizations, Wireless Networks, Financial and Time Series Prediction, Image Processing, Toxicology, Machine Control, Software Engineering, Information Management, Picture Compression, Noise Removal, Social Network Analysis