AIMC Topic: Fuzzy Logic

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Effective modelling of hydrogen and energy recovery in microbial electrolysis cell by artificial neural network and adaptive network-based fuzzy inference system.

Bioresource technology
This study aims to analyze and model cathodic H recovery (r), coulombic efficiency (CE) with inputs of voltage, electrical conductivity (EC) and anode potential, and H production rate and total energy recovery with inputs of r and CE in a microbial e...

Moonlighting Proteins in the Fuzzy Logic of Cellular Metabolism.

Molecules (Basel, Switzerland)
The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how the...

Optimal Selection of Sewage Treatment Technologies in Town Areas: A Coupled Multi-Criteria Decision-Making Model.

Environmental management
In recent years, the development of sewage treatment technologies has made many treatment options available in towns. Selecting the most appropriate alternative (MAA) can make the best use of existing resources to achieve the optimal effect, which ha...

Performance comparison of wavelet neural network and adaptive neuro-fuzzy inference system with small data sets.

Journal of molecular graphics & modelling
In this work, performance of wavelet neural network (WNN) and adaptive neuro-fuzzy inference system (ANFIS) models were compared with small data sets by different criteria such as second order corrected Akaike information criterion (AICc), Bayesian i...

Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index.

Environmental science and pollution research international
In recent decades, various conventional techniques have been formulated around the world to evaluate the overall water quality (WQ) at particular locations. In the present study, back propagation neural network (BPNN) and adaptive neuro-fuzzy inferen...

LogicNet: probabilistic continuous logics in reconstructing gene regulatory networks.

BMC bioinformatics
BACKGROUND: Gene Regulatory Networks (GRNs) have been previously studied by using Boolean/multi-state logics. While the gene expression values are usually scaled into the range [0, 1], these GRN inference methods apply a threshold to discretize the d...

Neuro-fuzzy patch-wise R-CNN for multiple sclerosis segmentation.

Medical & biological engineering & computing
The segmentation of the lesion plays a core role in diagnosis and monitoring of multiple sclerosis (MS). Magnetic resonance imaging (MRI) is the most frequent image modality used to evaluate such lesions. Because of the massive amount of data, manual...

An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm.

Sensors (Basel, Switzerland)
The herpesvirus, polyomavirus, papillomavirus, and retrovirus families are associated with breast cancer. More effort is needed to assess the role of these viruses in the detection and diagnosis of breast cancer cases in women. The aim of this paper ...

Regional Water Resources Security Evaluation Based on a Hybrid Fuzzy BWM-TOPSIS Method.

International journal of environmental research and public health
Nowadays, water resource security is becoming increasingly prominent, and this problem is a primary bottleneck restricting China's future sustainable development. It is difficult to come to a unified conclusion on water resources security, and applic...

Fully multi-target segmentation for breast ultrasound image based on fully convolutional network.

Medical & biological engineering & computing
Ultrasound image segmentation plays an important role in computer-aided diagnosis of breast cancer. Existing approaches focused on extracting the tumor tissue to characterize the tumor class. However, other tissues are also helpful for providing the ...