results multilayer perceptron (mlp) artificial neural network (ann) model with a 1-6-1 structure was chosen which explained 97% and 95% of kd and koc variances, respectively. the only input data was soil organic carbon content. conclusions based on this study, the ann method is a promising alternative for conventional methods in modeling and estimating sorption coefficients in relation to soil ...

background: reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in fisher 344 (f344) rats, occasioned by ingestion of malathion. methods: it was re...

conclusions results showed that ann is a powerful tool for predicting sorption coefficients using soil organic carbon content variations. results the multilayer perceptron (mlp) artificial neural networks (ann) model with 1-6-1 layout, predicted nearly 98% of the variance of kd as well as 94% of the koc variations with soil organic carbon content. materials and methods data of this study were d...

Concepts across and explain how they are used in actual, fielded systems.Author: interes Date: 2014-01-04 15: 02: 27. Tim Jones, Artificial Intelligence: A Systems Approach English 2008 ISBN: 0763773379 500 pages PDF 8.storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical. Artificial Intelligence AI is a big field, and this is a big book.The history ...

Abstract This paper develops an account of trustworthy AI. Its central idea is that whether AIs are a matter they live up to their function-based obligations. We argue this serves advance the literature in couple important ways. First, it provide rationale for why range properties widely assumed scientific literature, as well policy, be required AI, such safety, justice, and explainability, (of...

Embedded artificial intelligence (AI) seamlessly integrates AI into everyday devices. By bringing closer to the data source, embedded empowers real-time decision making, enhanced efficiency, and new possibilities across diverse domains.