As wind turbines more widely used with newer manufactured types and larger electrical power scales, a brief mathematical modelling for these operating curves is needed optimal site matching selections. In this paper, 24 commercial different ratings manufactures are modelled using single cumulative probability density functions equations. A new mean of composite function better accuracy. Invasiv...

Exotic invasive plants present one of the greatest challenges to natural resource management. These weeds can alter entire communities and ecosystems, substantially degrading important ecosystem services such as forage for wild and domestic herbivores, water and soil quality, recreational values, and wildlife habitat. Traditionally, weed management in natural areas has focused on removing the t...

Management of damaging invasive plants is often undertaken by multiple decision makers, each managing only a small part of the invader's population. As weeds can move between properties and re-infest eradicated sites from unmanaged sources, the dynamics of multiple decision makers plays a significant role in weed prevalence and invasion risk at the landscape scale. We used a spatially explicit ...

The direct negative effects of invasive plant species on agriculture and biodiversity are well known, but their indirect effects on human health, and particularly their interactions with disease-transmitting vectors, remains poorly explored. This study sought to investigate the impact of the invasive Neotropical weed Parthenium hysterophorus and its toxins on the survival and energy reserves of...

Predicting energy consumption has been a substantial topic because of its ability to lessen wastage and establish an acceptable overall operational efficiency. Thus, this research aims at creating meta-heuristic-based method for autonomous simulation heating cooling loads buildings. The developed is envisioned on two tiers, whereas the first tier encompasses use set meta-heuristic algorithms am...

Evolutionary Algorithms (EAs) are a fascinating branch of computational intelligence with much potential for use in many application areas. The fundamental principle of EAs is to use ideas inspired by the biological mechanisms observed in nature, such as selection and genetic changes, to find the best solution for a given optimization problem. Generally, EAs use iterative processes, by growing ...