soft-computing

fuzzylite: a fuzzy logic control library in C++

jfuzzylite: a fuzzy logic control library in Java

pyfuzzylite: a fuzzy logic control library in Python

A collection of Benchmark functions for numerical optimization problems. Framework of OPtimization FUnction in NUmpy (opfunu)

Type 1 and Interval Type 2 Fuzzy Logic Systems in Python

A soft computing method based web project which helps in predicting the disease based on the symptoms of the patient. Also informs the patients about nearby doctors availability and precautions to be taken. The heart of the project is Fuzzy Logic , a soft computing technique which makes use of knowledge base made by the experts(doctors in this case) to predict the disease severity.

(Code) A new workload prediction model using extreme learning machine and enhanced tug of war optimization

SOFT COMPUTING TECHNIQUES PROJECTS ARCHIVE

📈 Desktop app for testing and ploting fuzzy operators

Implementation of Online Sequential Extreme Learning Machine

Lab experiments on Neural Networks for Undergraduate ECE Students, NIT Rourkela

Optimization algorithms, mostly in Python (both from scratch and by using modules)

(Code IQSO-MLP) nQSV-Net: a novel queuing search variant for global space search and workload modeling

A soft computing method based web project which helps in predicting the disease based on the symptoms of the patient. Also informs the patients about nearby doctors availability and precautions to be taken. The heart of the project is Fuzzy Logic , a soft computing technique which makes use of knowledge base made by the experts(doctors in this case) to predict the disease severity.

This is a hybrid intelligent sampling technique to tackle class-imbalance in real world datasets. To know more about it please refer the link: https://www.sciencedirect.com/science/article/pii/S1568494619300924. Cite our paper, if you are using it in your research work. The citation of our paper is: Susan, Seba, and Amitesh Kumar. "SSOMaj-SMOTE-SSOMin: Three-step intelligent pruning of majority and minority samples for learning from imbalanced datasets." Applied Soft Computing 78 (2019): 141-149.

Contains submissions of the Soft Computing Elective Course at IIITA.

Soft Computing Project by Shoffiyah (140810160057) and Patricia (140810160065).

Project for the subject Soft computing

This is a hybrid intelligent sampling technique to tackle class-imbalance in real world datasets. To know more about it please refer the link: https://www.sciencedirect.com/science/article/pii/S1568494619300924. Cite our paper, if you are using it in your research work. The citation of our paper is: Susan, Seba, and Amitesh Kumar. "SSOMaj-SMOTE-SSOMin: Three-step intelligent pruning of majority and minority samples for learning from imbalanced datasets." Applied Soft Computing 78 (2019): 141-149.

Efficient Time-series Forecasting using Neural Network and Opposition-based Coral Reefs Optimization

SPPU LP4 Codes - Soft Computing and Optimization Algorithms (SCOA)

⏰ A machine-learning-based analog clock recognition and time detection app developed during the Soft Computing university course.

Everything I've done (and managed to keep!) during my time at IIIT Allahabad and earlier.

Functional Link Adaptive Bacterial Foraging using Life Cycle and Social Learning

Human disease diagonosis using fuzzy implementation

Fuzzy controler for dynamic traffic lights

This is a hybrid implementation of oversampling method Synthetic Minority Oversampling Technique (SMOTE) and undersampling method called Sample Subset Optimization and Particle Swarm Optimization (SSO-PSO) to solve Imbalanced data problem.