AIMC Topic: Environmental Monitoring

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Modelling the presence and identifying the determinant factors of dominant macroinvertebrate taxa in a karst river.

Environmental monitoring and assessment
Modelling the macroinvertebrate community is important for evaluating the status of aquatic ecosystem health. Alternative to physical-based approaches, this study proposed two data-driven methods, support vector machine (SVM) and artificial neural ne...

Evaluation of a Home Biomonitoring Autonomous Mobile Robot.

Computational intelligence and neuroscience
Increasing population age demands more services in healthcare domain. It has been shown that mobile robots could be a potential solution to home biomonitoring for the elderly. Through our previous studies, a mobile robot system that is able to track ...

Modeling the BOD of Danube River in Serbia using spatial, temporal, and input variables optimized artificial neural network models.

Environmental monitoring and assessment
This paper describes the application of artificial neural network models for the prediction of biological oxygen demand (BOD) levels in the Danube River. Eighteen regularly monitored water quality parameters at 17 stations on the river stretch passin...

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.

Computational intelligence and neuroscience
The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parame...

Typha latifolia (broadleaf cattail) as bioindicator of different types of pollution in aquatic ecosystems-application of self-organizing feature map (neural network).

Environmental science and pollution research international
The contents of Cd, Cu, Fe, Mn, Ni, Pb, and Zn in leaves of Typha latifolia (broadleaf cattail), water and bottom sediment from 72 study sites designated in different regions of Poland were determined using atomic absorption spectrometry. The aim of ...

Artificial neural network models for prediction of daily fine particulate matter concentrations in Algiers.

Environmental science and pollution research international
Neural network (NN) models were evaluated for the prediction of suspended particulates with aerodynamic diameter less than 10-μm (PM10) concentrations. The model evaluation work considered the sequential hourly concentration time series of PM10, whic...

Use of a Robotic Sampler (PIPER) for Evaluation of Particulate Matter Exposure and Eczema in Preschoolers.

International journal of environmental research and public health
While the association of eczema with asthma is well recognized, little research has focused on the potential role of inhalable exposures and eczema. While indoor air quality is important in the development of respiratory disease as children in the U....

An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland.

Environmental monitoring and assessment
A predictive model for streamflow has practical implications for understanding the drought hydrology, environmental monitoring and agriculture, ecosystems and resource management. In this study, the state-or-art extreme learning machine (ELM) model w...

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

Sensors (Basel, Switzerland)
Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as...

Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy.

Marine pollution bulletin
Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 cr...