Πλοήγηση ανά Θέμα "Fuzzy cognitive map"
Αποτελέσματα 1-19 από 19
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Application of Fuzzy Cognitive Maps to water demand prediction
(2015)This article is focused on the issue of learning of Fuzzy Cognitive Maps designed to model and predict time series. The multi-step supervised-learning based-on-gradient methods as well as population-based learning, with ... -
Bagged nonlinear Hebbian learning algorithm for fuzzy cognitive maps working on classification tasks
(2012)Learning of fuzzy cognitive maps (FCMs) is one of the most useful characteristics which have a high impact on modeling and inference capabilities of them. The learning approaches for FCMs are concentrated on learning the ... -
Circular bio-economy via energy transition supported by Fuzzy Cognitive Map modeling towards sustainable low-carbon environment
(2020)Several energy transition plans attempt to establish low-carbon practices towards a circular bio-economy in order to reduce greenhouse gas emissions. However, most actions only try to assuage the impacts of climate change ... -
Classifying mammography images by using fuzzy cognitive maps and a new segmentation algorithm
(2018)Mammography is one of the best techniques for the early detection of breast cancer. In this chapter, a method based on fuzzy cognitive map (FCM) and its evolutionary-based learning capabilities is presented for classifying ... -
Constructive Fuzzy Cognitive Map for Depression Severity Estimation
(2022)Depression is a common and serious medical disorder that negatively affects the mood and the emotions of people, especially adolescents. In this paper, a novel framework for automatically creating Fuzzy Cognitive Maps ... -
Decision-making process for photovoltaic solar energy sector development using fuzzy cognitive map technique
(2020)Photovoltaic Solar Energy (PSE) sector has sparked great interest from governments over the last decade towards diminution of world’s dependency to fossil fuels, greenhouse gas emissions reduction and global warming ... -
Effective Brain Connectivity for fNIRS with Fuzzy Cognitive Maps in Neuroergonomics
(2022)Effective connectivity (EC) among functional near-infrared spectroscopy (fNIRS) signals is a quantitative measure of the strength of influence between brain activity associated with different regions of the brain. Evidently, ... -
Exploring an ensemble of methods that combines fuzzy cognitive maps and neural networks in solving the time series prediction problem of gas consumption in Greece
(2019)This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim ... -
Exploring brazilian photovoltaic solar energy development scenarios using the fuzzy cognitive map wizard tool
(2020)Photovoltaic Solar Energy (PSE) sector has gained great attention during the last decades due to its significant role in the transition to sustainable energy systems. As a viable energy option, PSE has the potential to ... -
From undirected structures to directed graphical lasso fuzzy cognitive maps using ranking-based approaches
(2020)Fuzzy cognitive maps (FCMs) have gained popularity within the scientific community due to their capabilities in modelling and decision making for complex problems. However, learning FCM models automatically from data without ... -
Fuzzy cognitive map-based modeling of social acceptance to overcome uncertainties in establishing waste biorefinery facilities
(2018)Sustainable Waste Biorefinery Facilities (WBFs) represent multifactorial systems that necessitate the organization, cooperation and the acceptance of different social stakeholders. However, these attempts have become targets ... -
Fuzzy cognitive maps and multi-step gradient methods for prediction: Applications to electricity consumption and stock exchange returns
(2015)The paper focuses on the application of fuzzy cognitive map (FCM) with multi-step learning algorithms based on gradient method and Markov model of gradient for prediction tasks. Two datasets were selected for the implementation ... -
Implementing fuzzy cognitive maps with neural networks for natural gas prediction
(2018)The goal of this research study is to test the hardiness of a novel hybrid computational intelligence model in day-ahead natural gas demand prediction. The proposed model combines an evolutionary learned FCM method with a ... -
Introducing Fuzzy Cognitive Maps for decision making in precision agriculture
(2007)A Fuzzy Cognitive Maps (FCMs) is a modelling methodology based on exploiting knowledge and experience. It comprises the main advantages of fuzzy logic and neural networks, representing a graphical model that consists of ... -
Management of uncomplicated urinary tract infections using fuzzy cognitive maps
(2009)Urinary Tract Infection (UTI) is a bacterial infection that affects any part of the urinary tract. It can be classified as uncomplicated (patients with urinary tracts that are normal from both structural and functional ... -
Multi-robot exploration using dynamic fuzzy cognitive maps and ant colony optimization
(2020)An application field of Multi-Robot Systems (MRS) is within victim rescue operations. The main challenge faced by disaster rescue teams is response time. The chances of finding survivors decrease significantly over time ... -
A novel medical decision support system based on fuzzy cognitive maps enhanced by intuitive and learning capabilities for modeling uncertainty
(2018)In this paper, an active Hebbian learning (AHL) for intuitionistic fuzzy cognitive map (iFCM) is proposed for grading the celiac. This method performs the diagnosis procedure automatically, and it is more suitable for ... -
Retrieving sparser fuzzy cognitive maps directly from categorical ordinal dataset using the graphical lasso models and the MAX-threshold algorithm
(2020)Learning FCM models from data without any a priori knowledge and expert intervention remains a considerable problem. This research study utilizes a fully data-based learning method (the glassoFCM) for automatic design of ... -
Soft computing approaches for urban water demand forecasting
(2016)This paper presents an integrated framework for water resources management at urban level which consists of a Neuro-Fuzzy and Fuzzy Cognitive Map-based, (FCM) decision support system (DSS) based on multiple objectives and ...