In this study we apply two methods for data collection that are relatively new in the field of atmospheric science. The two developed methods are designed to collect essential geo-localized information to be used as input data for a high resolution e...
International journal of environmental research and public health
Jul 10, 2018
Dispersion prediction plays a significant role in the management and emergency response to hazardous gas emissions and accidental leaks. Compared with conventional atmospheric dispersion models, machine leaning (ML) models have both high accuracy and...
In the past decade, a rich repertoire of soft robots, designed from biomimetic and intuitive approaches, has been developed to overcome challenges faced by their rigid-bodied counterparts. However, these design approaches are greatly limited by the d...
BMC medical informatics and decision making
Jul 6, 2018
BACKGROUND: The use of knowledge models facilitates information retrieval, knowledge base development, and therefore supports new knowledge discovery that ultimately enables decision support applications. Most existing works have employed machine lea...
Neural networks : the official journal of the International Neural Network Society
Jul 5, 2018
This paper is concerned with the synchronization problem for an array of memristive neural networks with inertial term, linear coupling and time-varying delay. Since parameters in the connection weight matrices are state-dependent, that is to say, th...
The efficient operation of wastewater treatment plants (WWTPs) is key to ensuring a sustainable and friendly green environment. Monitoring wastewater processes is helpful not only for evaluating the process operating conditions but also for inspectin...
Cell-penetrating peptides (CPPs) can enter cells as a variety of biologically active conjugates and have various biomedical applications. To offset the cost and effort of designing novel CPPs in laboratories, computational methods are necessitated to...
Environmental science and pollution research international
Jun 29, 2018
In this study, the neural networks are used to predict and explain the behavior of different edaphological variables in the adsorption and retention of heavy metals, both isolated and competing. A comparison with the results obtained using multiple r...
This paper addresses a chaos kernel function for the relevance vector machine (RVM) in EEG signal classification, which is an important component of Brain-Computer Interface (BCI). The novel kernel function has evolved from a chaotic system, which is...
In the present study three different types of neural models: multi-layer perceptron (MLP), generalized regression neural network (GRNN) and radial basis function (RBF) has been used to predict the exergetic efficiency of roughened solar air heater. T...