Eco-Friendly Incorporation of Crumb Rubber and Waste Bagasse Ash in Bituminous Concrete Mix.

The consumption of waste materials in the construction sector is a sustainable approach that helps in reducing the environmental pollution and decreases the construction cost. The present research work emphasizes the mechanical properties of bituminous concrete mix prepared with crumb rubber (CR) and waste sugarcane bagasse ash (SCBA). For the preparation of bituminous concrete mix specimens with CR and SCBA, the effective bitumen content was determined using the Marshall Mix design method.

Multigene Expression Programming Based Forecasting the Hardened Properties of Sustainable Bagasse Ash Concrete.

The application of multiphysics models and soft computing techniques is gaining enormous attention in the construction sector due to the development of various types of concrete. In this research, an improved form of supervised machine learning, i.e.

Proposed formulation of surface water quality and modelling using gene expression, machine learning, and regression techniques.

The rising water pollution from anthropogenic factors motivates further research in developing water quality predicting models. The available models have certain limitations due to limited timespan data and the incapability to provide empirical expressions. This study is devoted to model and derive empirical equations for surface water quality of upper Indus river basin using a 30-year dataset with machine learning techniques and then to determine the most reliable model capable to accurately predict river water quality.

Predicting hydrologic responses to climate changes in highly glacierized and mountainous region Upper Indus Basin.

The Upper Indus Basin (UIB) is a major source of supplying water to different areas because of snow and glaciers melt and is also enduring the regional impacts of global climate change. The expected changes in temperature, precipitation and snowmelt could be reasons for further escalation of the problem. Therefore, estimation of hydrological processes is critical for UIB.