Soft computing is an umbrella term used to describe types of algorithms that produce approximate solutions to unsolvable high-level problems in computer science. Typically, traditional hard-computing algorithms heavily rely on concrete data and mathematical models to produce solutions to problems. Soft computing was coined in the late 20th century.[1] During this period, revolutionary research in three fields greatly impacted soft computing. Fuzzy logic is a computational paradigm that entertains the uncertainties in data by using levels of truth rather than rigid 0s and 1s in binary. Next, neural networks which are computational models influenced by human brain functions. Finally, evolutionary computation is a term to describe groups of algorithm that mimic natural processes such as evolution and natural selection.
In the context of artificial intelligence and machine learning, soft computing provides tools to handle real-world uncertainties. Its methods supplement preexisting methods for better solutions. Today, the combination with artificial intelligence has led to hybrid intelligence systems that merge various computational algorithms. Expanding the applications of artificial intelligence, soft computing leads to robust solutions. Key points include tackling ambiguity, flexible learning, grasping intricate data, real-world applications, and ethical artificial intelligence.[2][3]
^Zadeh, Lotfi A. (March 1994). "Fuzzy logic, neural networks, and soft computing". Communications of the ACM. 37 (3): 77–84. doi:10.1145/175247.175255. ISSN 0001-0782.
^Kecman, Vojislav (2001). Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models. MIT Press. ISBN 978-0-262-11255-0.
Softcomputing is an umbrella term used to describe types of algorithms that produce approximate solutions to unsolvable high-level problems in computer...
The Journal of SoftComputing in Civil Engineering is a quarterly peer-reviewed open-access scientific journal covering softcomputing applications in...
Approximation", Applications of SoftComputing: From Theory to Praxis, Springer, Series: Advances in Intelligent and SoftComputing, Volume 58/2009, ISBN 978-3-540-89618-0...
Patil, S. H. (2005). "SoftComputing- A Fuzzy Logic Approach". In Bharati Vidyapeeth College of Engineering (ed.). SoftComputing. Allied Publishers. p...
biological evolution, and the subfield of artificial intelligence and softcomputing studying these algorithms. In technical terms, they are a family of...
dedicated server, managed hosting, and cloud computing provider, founded in 2005 and acquired by IBM in 2013. SoftLayer initially specialized in hosting workloads...
by arguing that the first one is based on softcomputing methods, whereas AI is based on hard computing ones. According to Bezdek (1994), while Computational...
on softcomputing, granular computing and their roles in the conception, design and utilization of information/intelligent systems. SoftComputing, 1998...
Issue on 'Emerging Trends in SoftComputing - Memetic Algorithm' Archived 2011-09-27 at the Wayback Machine, SoftComputing Journal, Completed & In Press...
Systems Engineering: Theory and Practice, Studies in Fuzziness and SoftComputing, vol. 181, Germany: Springer Verlag, pp. 53–83, CiteSeerX 10.1.1.161...
Unconventional computing is computing by any of a wide range of new or unusual methods. It is also known as alternative computing. The term unconventional...
way to implement massive parallelism in computing and can likewise be applied to in-memory computing. A soft microprocessor and its surrounding peripherals...
originated with Rosalind Picard's 1995 paper on affective computing and her book Affective Computing published by MIT Press. One of the motivations for the...
seen as soft sensors include Kalman filters. More recent implementations of soft sensors use neural networks or fuzzy computing. Examples of soft sensor...
and SoftComputing, vol. 131, Springer-Verlag Mordeson, J.N., Bhutani, K.R., Rosenfeld, A. (2005) Fuzzy Group Theory. Studies in Fuzziness and Soft Computing...
in (f, A). A systematic literature review on soft set theory was published in the journal Neural Computing and Applications in February 2024. One of the...
Neuromorphic computing is an approach to computing that is inspired by the structure and function of the human brain. A neuromorphic computer/chip is...
approximation. Softcomputing was introduced in the late 1980s and most successful AI programs in the 21st century are examples of softcomputing with neural...
optimization tools have several limitations. Therefore, in the framework of softcomputing, genetic algorithms (GAs) and genetic programming (GP) methods have...
numbers. Fuzzy set Lotfi Zadeh Perceptual computing Type-2 fuzzy sets and systems L. A. Zadeh, “Fuzzy logic = computing with words,” IEEE Trans. on Fuzzy Systems...
evolution method". Proceedings of the 8th International Conference on SoftComputing (MENDEL). Brno, Czech Republic. pp. 11–18. Zaharie, D. (2002). "Critical...
coordinated by the joint IAHR, IWA, IAHS Hydroinformatics Section. Classic Soft-Computing Techniques is the first volume of the three, in the Handbook of HydroInformatics...
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