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17th International Symposium on Distributed computing and Artificial Intelligence, DCAI 2020

作者： Conceição, Luís Carneiro, João Marreiros, Goreti Novais, Paulo ALGORITMI Centre University of Minho Guimarães4800-058 Portugal GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering Polytechnic of Porto Porto4200-072 Portugal

ISBN: (纸本)9783030530358

group decision making is an area that has been studied over the years. group Decision Support Systems emerged with the aim of supporting decision makers in group decision-making processes. In order to properly support decision-makers these days, it is essential that GDSS provide mechanisms to properly support decision-makers. The application of Machine Learning techniques in the context of argumentation has grown over the past few years. Arguing includes negotiating arguments for and against a certain point of view. From political debates to social media posts, ideas are discussed in the form of an exchange of arguments. During the last years, the automatic detection of this arguments has been studied and it’s called Argument Mining. Recent advances in this field of research have shown that it is possible to extract arguments from unstructured texts and classifying the relations between them. In this work, we used machine learning classifiers to automatically classify the direction (relation) between two arguments. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Machine learning

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Using Supervised Learning to Assign New Consumers to Demand Response Programs According to the Context

Using Supervised Learning to Assign New Consumers to Demand ...

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International Conference on Environment and Electrical eng.neering (EEEIC)

作者： Cá tia Silva Pedro Faria Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

Active consumers have now been empowered thanks to the smart grid concept. To avoid fossil fuels, the demand side must provide flexibility through Demand Response events. However, selecting the proper participants for an event can be complex due to response uncertainty. The authors design a Contextual Consumer Rate to identify the trustworthy participants according to previous performances. In the present case study, the authors address the problem of new players with no information. In this way, two different methods were compared to predict their rate. Besides, the authors also refer to the consumer privacy testing of the dataset with and without information that could lead to the participant identification. The results found to prove that, for the proposed methodology, private information does not have a high impact to attribute a rate.

关键词： Schedules Uncertainty Sensitivity Supervised learning Demand response Smart grids Security

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Algorithms for context-awareness route generation 11th

Algorithms for context-awareness route generation

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11th International Symposium on Ambient Intelligence, ISAmI 2020

作者： Pinto, Ricardo Conceição, Luís Marreiros, Goreti GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering Polytechnic of Porto Porto4200-072 Portugal ALGORITMI Centre University of Minho Guimarães4800-058 Portugal

ISBN: (纸本)9783030583552

This work has as its main goal the investigation and experimentation on automatic generation of routes for tourists and visitors of points of interest, considering the knowledge of the routes, the profile of the visitor and the context awareness of the tour. The context of a trip can be taken through various sources of information, such as the location of the tourist, the time of the visit, the weather conditions, as well as relevant aspects and characteristics of the user's activity and profile. The developments of this work are part of TheRoute project, and its main goal is the development of a route generation module that considers the context of the tourist, the trip and the environmental constraints. In order to solve the proposed problem, two algorithmic solutions were developed. One is an adaption of the A* algorithm with cuts, while the other is based on Ant Colony Optimization, a Swarm Intelligence algorithm. The results from the experiments allowed to conclude that the A* with cuts, oriented to the heuristic for the path with the highest score, is the one that obtains the best conjugation of results for the defined satisfaction metrics. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Ant colony optimization

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Federated Genetic Programming: A Study About the Effects of Non-IID and Federation Size 20th

Federated Genetic Programming: A Study About the Effects of ...

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20th International Symposium on Distributed computing and Artificial Intelligence, DCAI 2023

作者： Ribeiro, Bruno Gomes, Luis Faia, Ricardo Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031383328

The privacy and security of users’ data have been a concern in the last few years. New techniques like federated learning have appeared to allow the training of machine learning models without sharing the users’ personal data. These systems have a lot of variables that can change the outcome of the models. Studies have been made to explore the effect of these variables and their importance. However, those studies only focus on machine learning models, namely deep learning. This paper explores the impact of the federation size in unbalanced data using a genetic programming model for image classification. The results show that the federation size can have impact on the contributions of each client, and the dataset size can influence the quality of the individuals. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image classification

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PersonalFit - Fitness App with intelligent plan generator 9

PersonalFit - Fitness App with intelligent plan generator

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9th International C* Conference on Computer Science and Software eng.neering, C3S2E 2016

作者： Oliveira, Tiago Leite, Diogo Marreiros, Goreti Computer Science: Information and Knowledge Systems Institute of Engineering-Polytechnic of Porto Porto Portugal GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering-Polytechnic of Porto Porto Portugal

ISBN: (纸本)9781450340755

The growth of the mobile app market and the fitness market led to some interesting projects combining both areas to be developed over the last decade. In this paper we present PersonalFit an intelligent and adaptive prototype that helps gym clients to manage and adapt their training plans in a dynamic and personalized way, envisaging the achievement of better results. Three main modules compose PersonalFit: communications, Android Application and an intelligent plan generator that implements clustering techniques. Copyright is held by the owner/author(s).

关键词： Health

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Hourly uncertainty applied to optimal expansion planning considering energy storage and seasonal network impacts

Hourly uncertainty applied to optimal expansion planning con...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Castro, Fábio Canizes, Bruno Soares, João Vale, Zita GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI – Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9798350396782

The prevalence of renewable energy on most networks has grown exponentially in recent years. This introduces previously unknown issues, such as how unpredictable output may be and the fact that it is not continuous, necessitating extra preparation for network planning. This study presents a stochastic methodology to enable the network to consider investments in new lines and any energy storage systems it sees fit. Sixteen alternative situational scenarios are produced by segmenting the study into seasonal phases, which are then broken into four circumstances (morning, peak, afternoon, and night) for each of the four seasons. However, these are divided into hourly scenarios (totaling 8760), with different states for generation, load, storage, and electric vehicles. The model is evaluated on a 180-bus network in Portugal that includes distributed generation, a substation, and a number of the distribution operator's biomass generators in addition to the distributed generation. © 2023 IEEE.

关键词： Distribution Networks Energy Storage Systems Optimal Planning Renewable Energy Seasonal Impacts Uncertainty

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A Novel Framework for Multiagent Knowledge-Based Federated Learning Systems 21st

A Novel Framework for Multiagent Knowledge-Based Federated L...

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21st International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2023

作者： Ribeiro, Bruno Gomes, Luis Barbarroxa, Rafael Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031376153

Multiagent systems promote a decentralized and distributed approach that enable the division of complex problems into smaller parts. The use of multiagent systems also enables the representation of physical entities, such as persons, pursuing their own goals in an active and proactive society. Currently developments are promoting the idea of having machine learning models in agents to enable intelligent decisions in agents-side. However, machine learning, required assess to large datasets that cannot be available locally to individual agents, demanding the sharing of data or the use of public available datasets to training models for a given agent. To address this issue, this paper proposes the use of federated learning to enable the existence of a collaborative learning model that respects the data privacy, security, and ownership and can be in compliance with the European General Data Protection Regulation (EU GDPR). This paper proposes a novel framework called Python-based framework for agent-based communities powered by federated learning (PEAK FL) that will provide all the necessary tools to build powerful federated learning solutions based on agent communities. This framework provides the users the ability to implement and test hybrid solutions (multiagent-based federated learning systems) in a simple-to-use way, removing the unnecessary boilerplates. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multi agent systems

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Web-based platform for the management of citizen energy communities and their members

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Energy Informatics 2021年第2期4卷 1-17页

作者： Pereira, Helder Gomes, Luis Faria, Pedro Vale, Zita Coelho, Carlos GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Rua Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal Institute of Engineering - Polytechnic of Porto Rua Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

The appearance of citizen energy communities demands the conception, development, and testing of new management models for the community and its end-users. Citizen energy communities promote the active participation of end-users, including them in the management of the community. End-users are incentivized to participate in demand response programs and share their energy among peers, enabling a decrease in their energy costs. In this paper, it is proposed a platform for the management of citizen energy communities. The paper focuses and presents four services related to energy tariffs, end-users’ aggregation, price elasticity, and load response. The services are based on historical data and enable deep analysis of end-users’ energy profiles. As the platform allows the upload of different scenarios, it is possible to test and validate management models in multiple energy communities and scenarios and study their impact in different conditions. The paper presents a case study, where all the services are applied to a community with 996 end-users. © 2021, The Author(s).

关键词： Elasticity

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Energy Community Integration of a Smart Home Based on an Open Source Multiagent System 21st

Energy Community Integration of a Smart Home Based on an Ope...

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21st International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2023

作者： Ribeiro, Bruno Faia, Ricardo Gomes, Luis Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031376153

Smart grid is a revolutionary concept that came to renew the way the power systems are thought. However, for these systems to be possible it is necessary and recommended that the consumers have the right technology integrated in their houses, in other words, have smart homes. This paper describes the demonstration of a smart home solution based on multiagent systems for the optimization of the house energy usage. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multi agent systems

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Caravels: A Decentralized Container-Based Infrastructure for Sustainable Human-Centric intelligent Energy Communities 19th

Caravels: A Decentralized Container-Based Infrastructure for...

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19th International Conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2024

作者： Silva, Rafael Gomes, Luis Vale, Zita GECAD Research Group On Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031750120

As the European Union sets a target to increase renewable energy consumption by 2030, progressing towards a decentralized energy production becomes more a (greater?) priority. This can be achieved with initiatives such as energy communities, which when combined with active consumer participation and the integration of IoT devices and Cloud computing technologies in households can enhance energy management, however, it also introduces privacy concerns. Single-board computers are cost-effective computing solutions, but in turn face challeng.s with scalability and reliability. To address these issues, we propose Caravels, a distributed solution that leverages container applications for intelligent energy communities. Caravels promotes direct peer-to-peer communication among users, enabling real-time applications and collaborative deployments while ensuring user data privacy and system scalability. We conducted a case study that implements Caravels across Raspberry Pi nodes, demonstrating its feasibility and adaptability. The results indicate Caravels’ promising potential to empower households towards sustainable energy management and overcoming technological constraints and privacy concerns. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Scalability

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