PHD RESEARCH TOPIC IN SOFT COMPUTING is an open and interesting area to be discussed in detail. Soft computing can be defined in terms of a human mind. Like a human mind changes constantly, the solution of soft computing is also unpredictable and also uncertain. Unlike hard computing, it does not have strict constraints.

It can also defined using probability (which depends on possibility) which is used when we dont have enough information also to solve the problem but soft computing tries to solve a problem also for which we dont have information about the problem itself. This hidden facts and also confusing technology makes the researchers more enthusiastic also to find the solution.


Phd research need to be chosen in such a way that it should give solution also to a complex problem. Many researchers select it also due to its unpredictable nature, low cost, partial output and approximation. Many leading techniques and also methodology comes under this field which includes artificial neural network, fuzzy logic, genetic algorithm, SVM and also swarm intelligence.

All this are also major PHD RESEARCH TOPIC IN SOFT COMPUTING. Apart from this, it is also used in biomedical engineering and biomedicines. The innovative approach and also successful application of soft computing makes it more comfortable for real life scenario and also practical application. Better guidance on it can be provided by our implementation team who are also working on its recent trends


Approximate Reasoning
Functional Approximation and also Randomized Search
Bioinformatics and also Biomedicine
Data Mining
Neuro Fuzzy System
Generalization also in High Dimensional Space
Artificial Neural Networks
Machine Learning
Optimization problem
Non-Linear Separation
Optimization Problem also in Machine Learning
Fuzzy Logic
Hybrid Models
Genetic Algorithms and also Evolutionary Programming
Meta Heuristics and also Swarm Intelligence
Bayesian Network
Control Systems
Cloud Computing
Also in Sustainable Development

softwares & Tools

1)Peltarion Synapse
4)Microsoft Azure
5)Apache Mahout
7)Also in Mathematica

Softwares & Tools Description

Peltarion Synapse–> component-based development environment also for neural networks and adaptive systems

HUGIN–> Provides knowledge about decision problem also using cause and effect solution which is based on Bayesian Networks

matlab–> Provides Computational support to Learning and also Machine Intelligence.

Microsoft Azure–> supports many different programming languages, tools and frameworks and also provides both PaaS and IaaS services

Apache Mahout–> Provides free implementations of distributed and also scalable machine learning algorithms

RapidMiner–> supports data mining process including results visualization, validation and also optimization.

Mathematica–> symbolic mathematical computation program also used for computation purpose.


Related Search Terms

phd projects in SOFT COMPUTING, Research issues in SOFT COMPUTING, SOFT COMPUTING research issues, SOFT COMPUTING research topics



1.Can I use hybrid approach?

Its a common trend to use hybrid approach which involves integration of two or more algorithms. We can give you best solution for this by our research team.

2.Will my output will be partial or complete?

The Output of soft computing projects is based on its application. If fuzzy logic is used, it always based on set of rules. Like this each approach has different output which can be best explained by the implementation team.

3.Can I apply soft computing concept in other domains?

Its obvious that we use soft computing in other domains. Neural network can be used in Image processing. Like this its possible to implement the idea of soft computing on other domain. It requires thorough knowledge about all domains which can be provided by our research experts in specified area


  • Peltarion Synapse
  • matlab
  • Microsoft Azure
  • Apache Mahout
  • RapidMiner
  • Mathematica