Estimation of compressive strength of high-strength concrete by random forest and M5P model tree approaches

High strength concrete (HSC) define as the concrete that meets a unique mixture of performance uniformity requirements that cannot be reached routinely using conventional constituents and regular mixing, placing, and curing events. The modeling of such type of concrete is very difficult. In this investigation, the performance of the random forest regression and M5P model tree were compared to estimate the 28th day compressive strength of the HSC. Total data set consists of 83 data out of which 70 % of the total dataset used to train the model and residual 30 % used to test the models. The accuracy of the models was depending upon the three performance evaluation parameters which are correlation coefficient (R), root mean square error (RMSE) and maximum absolute error (MAE). The results recommend that random forest regression is more accurate to predict the compressive strength as compare to M5P model tree. Sensitivity analysis indicates that water (W) and Silica fumes (SF) are the most valuable constituents of the HSC and compressive strength mainly depends on these constituents

Estimation of compressive strength of high-strength concrete by random forest and M5P model tree approaches

High strength concrete (HSC) define as the concrete that meets a unique mixture of performance uniformity requirements that cannot be reached routinely using conventional constituents and regular mixing, placing, and curing events. The modeling of such type of concrete is very difficult. In this investigation, the performance of the random forest regression and M5P model tree were compared to estimate the 28th day compressive strength of the HSC. Total data set consists of 83 data out of which 70 % of the total dataset used to train the model and residual 30 % used to test the models. The accuracy of the models was depending upon the three performance evaluation parameters which are correlation coefficient (R), root mean square error (RMSE) and maximum absolute error (MAE). The results recommend that random forest regression is more accurate to predict the compressive strength as compare to M5P model tree. Sensitivity analysis indicates that water (W) and Silica fumes (SF) are the most valuable constituents of the HSC and compressive strength mainly depends on these constituents

Revolutionary Role of Trichoderma in Sustainable Plant Health Management: A Review

The use of chemical pesticides in agricultural practices has led to significant concerns related to health and the environment in the last few decades. Consequently, there has been a growing interest in finding alternative approaches for controlling pests and diseases that are effective and environmentally friendly. Among these alternatives, Trichoderma harzianum has gained attention due to its remarkable ability to combat various crop pathogens in sustainable form. Biocontrol agents have gained prominence as eco-friendly substitutes for conventional chemical pesticides in disease management and crop improvement. T. harzianum, a common filamentous fungus, has emerged as a promising biocontrol agent due to its multifaceted strategies for suppressing diseases and promoting crop growth. T. harzianum fosters plant growth by aiding nutrient absorption, improving soil structure, and generating growth-promoting substances like auxins and cytokinins. Field studies have substantiated the efficacy of T. harzianum in managing a wide array of plant diseases caused by fungi, bacteria, and nematodes whether used as a seed treatment, soil application, or foliar spray, T. harzianum establishes a beneficial presence early in the plant's life cycle, providing enduring protection. In conclusion, T. harzianum holds immense potential as a biocontrol agent to sustainably safeguard crops. Trichoderma species play a pivotal role in managing plant diseases due to their versatile mechanisms. As global agriculture seeks alternatives to chemical pesticides, leveraging T. harzianum 's potential offers a valuable avenue toward resilient and environmentally safe crop production