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...

One of the effectual text classification approaches for learning extensive information is incremental learning. The big issue that occurs enhancing accuracy, as comprised a large number terms. In order to address this issue, new approach designed using proposed hybrid optimization algorithm named Henry Fuzzy Competitive Multi-verse Optimizer (HFCVO)-based Deep Maxout Network (DMN). Here, optima...

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 ...