Peer Reviewed Journals

A Novel Optimization Algorithm: Cascaded Adaptive Neuro-Fuzzy Inference System - International Journal of Fuzzy Systems

An Efficient Automatic Fruit-360 Image Identification and Recognition Using a Novel Modified Cascaded-ANFIS Algorithm

Projected Water Levels and Identified Future Floods: A Comparative Analysis for Mahaweli River, Sri Lanka

Water level prediction using soft computing techniques: A case study in the Malwathu Oya, Sri Lanka

Brain Activity Associated with the Planning Process during the Long-Time Learning of the Tower of Hanoi (ToH) Task: A Pilot Study

A Cascaded Adaptive Network-Based Fuzzy Inference System for Hydropower Forecasting

Machine Learning Techniques to Predict the Air Quality Using Meteorological Data in Two Urban Areas in Sri Lanka

Efficient and Low-Cost Skin Cancer Detection System Implementation with a Comparative Study Between Traditional and CNN-Based Models

Age Classification of Rice Seeds in Japan Using Gradient-Boosting and ANFIS Algorithms

Cascaded-ANFIS to simulate nonlinear rainfall–runoff relationship

Performance verification and latency time evaluation of hardware image processing module for appearance inspection systems using FPGA - Journal of Real-Time Image Processing

Forecasting PM10 levels in Sri Lanka: A comparative analysis of machine learning models PM10

Performance of machine learning models to forecast PM10 levels

Sensitivity analysis of parameters affecting wetland water levels: A study of a flood detention basin, Colombo, Sri Lanka

Justifying the prediction of major soil nutrients levels (N, P, and K) in cabbage cultivation

Artificial intelligence to predict soil temperatures by development of novel model - Scientific Reports

In-depth simulation of rainfall–runoff relationships using machine learning methods

Spatial mapping and analysis of forest fire risk areas in Sri Lanka – Understanding environmental significance

Analyzing the impact of socioeconomic indicators on gender inequality in Sri Lanka: A machine learning-based approach

Advancing water quality assessment and prediction using machine learning models, coupled with explainable artificial intelligence (XAI) techniques like shapley additive explanations (SHAP) for interpreting the black-box nature

AI-driven predictions of geophysical river flows with vegetation - Scientific Reports

Impact of economic indicators on rice production: A machine learning approach in Sri Lanka

A novel application with explainable machine learning (SHAP and LIME) to predict soil N, P, and K nutrient content in cabbage cultivation

Artificial intelligence to evaluate the impact of urban green and blue spaces on chlorophyll-a concentrations - Environmental Science and Pollution Research

Enhancing Water Level Prediction Using Ensemble Machine Learning Models: A Comparative Analysis - Water Resources Management

Leveraging level data for accurate downstream flow prediction in the Narmada River Basin with advanced machine learning models

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