Search results for "Heuristic"

showing 10 items of 476 documents

Identification of Key miRNAs in Regulation of PPI Networks

2020

In this paper, we explore the interaction between miRNA and deregulated proteins in some pathologies. Assuming that miRNA can influence mRNA and consequently the proteins regulation, we explore this connection by using an interaction matrix derived from miRNA-target data and PPI network interactions. From this interaction matrix and the set of deregulated proteins, we search for the miRNA subset that influences the deregulated proteins with a minimum impact on the not deregulated ones. This regulation problem can be formulated as a complex optimization problem. In this paper, we have tried to solve it by using the Genetic Algorithm Heuristic. As the main result, we have found a set of miRNA…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni0301 basic medicineOptimization problemSettore INF/01 - InformaticaHeuristic (computer science)Computer sciencemiRNA expression profiles Protein-protein interaction networks Genetic algorithmsComputational biologyGenetic algorithmsmiRNA expression profilesProtein-protein interaction networks03 medical and health sciencesIdentification (information)030104 developmental biologyPpi networkGenetic algorithmmicroRNAKey (cryptography)Set (psychology)
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Social-Behavioral Aware Optimization of Energy Consumption in Smart Homes

2018

Residential energy consumption is skyrocketing, as residential customers in the U.S. alone used 1.4 trillion kilowatt-hours in 2014 and the consumption is expected to increase in the next years. Previous efforts to limit such consumption have included demand response and smart residential environments. However, recent research has shown that such approaches can actually increase the overall energy consumption due to the numerous complex human psychological processes that take place when interacting with electrical appliances. In this paper we propose a social-behavioral aware framework for energy management in smart residential environments. We envision a smart home where appliances are int…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniConsumption (economics)Smart HomeInformation Systems and ManagementOperations researchbusiness.industryComputer scienceHeuristic (computer science)Energy management020209 energySocial-Behavioral aware OptimizationEnergy Consumption02 engineering and technologyEnergy consumptionDemand responseComputer Networks and CommunicationHome automation0202 electrical engineering electronic engineering information engineeringSet (psychology)businessInteger programming2018 14th International Conference on Distributed Computing in Sensor Systems (DCOSS)
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A genetic approach to the maximum common subgraph problem

2019

Finding the maximum common subgraph of a pair of given graphs is a well-known task in theoretical computer science and with considerable practical applications, for example, in the fields of bioinformatics, medicine, chemistry, electronic design and computer vision. This problem is particularly complex and therefore fast heuristics are required to calculate approximate solutions. This article deals with a simple yet effective genetic algorithm that finds quickly a solution, subject to possible geometric constraints.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniGenetic AlgorithmMaximum Common SubgraphTheoretical computer scienceOptimization problemSettore INF/01 - InformaticaComputer science0102 computer and information sciences02 engineering and technology01 natural sciencesTask (project management)Optimization Problem010201 computation theory & mathematicsSimple (abstract algebra)Genetic algorithm0202 electrical engineering electronic engineering information engineeringElectronic design020201 artificial intelligence & image processingHeuristicsProceedings of the 20th International Conference on Computer Systems and Technologies
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Enabling peer-to-peer User-Preference-Aware Energy Sharing Through Reinforcement Learning

2020

Renewable, heterogeneous and distributed energy resources are the future of power systems, as envisioned by the recent paradigm of Virtual Power Plants (VPPs). Residential electricity generation, e.g., through photovoltaic panels, plays a fundamental role in this paradigm, where users are able to participate in an energy sharing system and exchange energy resources among each other. In this work, we study energy sharing systems and, differently from previous approaches, we consider realistic user behaviors by taking into account the user preferences and level of engagement in the energy trades. We formulate the problem of matching energy resources while contemplating the user behavior as a …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniHeuristicbusiness.industryComputer scienceDistributed computingEnergy SharingPeer-to-peercomputer.software_genreReinforcement LearningBehavioral modelingElectric power systemElectricity generationDistributed generationReinforcement learningbusinesscomputerInteger programmingVirtual Power Plant
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A Reinforcement Learning Approach for User Preference-aware Energy Sharing Systems

2021

Energy Sharing Systems (ESS) are envisioned to be the future of power systems. In these systems, consumers equipped with renewable energy generation capabilities are able to participate in an energy market to sell their energy. This paper proposes an ESS that, differently from previous works, takes into account the consumers’ preference, engagement, and bounded rationality. The problem of maximizing the energy exchange while considering such user modeling is formulated and shown to be NP-Hard. To learn the user behavior, two heuristics are proposed: 1) a Reinforcement Learning-based algorithm, which provides a bounded regret and 2) a more computationally efficient heuristic, named BPT- ${K}…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMathematical optimizationCorrectnessComputer Networks and CommunicationsRenewable Energy Sustainability and the EnvironmentComputer scienceHeuristicUser modelingRegretBounded rationalityReinforcement learningCoal Energy exchange Energy Sharing Systems Green products Power generation Production Reinforcement Learning Renewable energy sources User Preference Virtual Power PlantsEnergy marketHeuristics
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Efficient tree construction for the multicast problem

2002

A new heuristic for the Steiner minimal tree problem is presented. The method described is based on the detection of particular sets of nodes in networks, the "hot spot" sets, which are used to obtain better approximations of the optimal solutions. An algorithm is also proposed which is capable of improving the solutions obtained by classical heuristics, by means of a stirring process of the nodes in solution trees. Classical heuristics and an enumerative method are used as comparison terms in the experimental analysis which demonstrates the capability of the heuristic discussed.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMinimisation (psychology)Mathematical optimizationMulticastHeuristicProcess (computing)STP multicast transmissionNetwork topologySteiner tree problemsymbols.namesakeTree (data structure)symbolsHeuristicsMathematicsITS'98 Proceedings. SBT/IEEE International Telecommunications Symposium (Cat. No.98EX202)
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Perché le teorie liberali moderate non devono temere la behavioral economics o la heuristics and biases psychology

2021

In this article I will explain the content of soime cognitive bias and the content of liberal theories. I will argument that people commit less cognitive errors than Conly and others think. Secondly, some behaviours that Conly and others think are cognitive bias are not. Finally, it is clear in the studies of Kahneman and Tversky that the majority of cognitive bias are not incorrigibles (in the correct sense of this word)

Settore IUS/20 - Filosofia Del Dirittoliberal theories mill mheuristics and biases smoke
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Distance Measures for Portfolio Selection

2017

The classical Markowitz approach to the portfolio selection problem (PSP) consists of selecting the portfolio that minimises the return variance for a given level of expected return. By solving the problem for different values of this expected return we obtain the Pareto efficient frontier, which is composed of non-dominated portfolios. The final user has to discriminate amongst these points by resorting to an external criterion in order to decide which portfolio to invest in. We propose to define an external portfolio that corresponds to a desired criterion, and to assess its distance from the Markowitz frontier in market allowing for short-sellings or not. We show that this distance is ab…

Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e FinanziarieMathematical optimizationSettore INF/01 - InformaticaComputer sciencePareto principleEfficient frontierMetaheuristicVariance (accounting)Financial modelPortfolio selectionDistance measuresMultiple criteriaDecision aidSettore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Order (exchange)PortfolioExpected returnMarkowitzSettore MAT/09 - Ricerca OperativaSelection (genetic algorithm)Distance measureIndex tracking
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Selection of Large Sub-Samples from the Continuous Sample of Working Lives Representative of the Benefits Provided by the Spanish Public Pension Syst…

2016

The Continuous Sample of Working Lives (CSWL) is a set of anonymized microdata with information about individuals taken from Spanish Social Security records. It provides very valuable information, which is used in many studies on labor economics and in the analysis of the Spanish public pension system. This article presents two major contributions: The first is an analysis of how representative CSWL is of the population of pensioners for the period 2005-2013. It is concluded that the CSWL does not follow the same distribution as the population with respect to some types of benefits, and that this happens in most waves. One of the reasons is that it is obtained by simple random sampling, so …

Social securityeducation.field_of_studyPensionComputer sciencePopulationSampling designEconometricsMicrodata (statistics)educationSimple random sampleRepresentativeness heuristicStratified samplingSSRN Electronic Journal
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Soft Computing Techniques for Portfolio Selection: Combining SRI with Mean-Variance Goals

2014

A fuzzy portfolio selection model is presented incorporating a socially responsible goal without discarding a priori financially good portfolios or weakening a priori the financial goals. Hence, the optimal portfolios it provides could be either efficient from the strictly financial point of view or non-efficient if leaving the efficient frontier substantially improves the degree of social responsibility. The model can be used to direct heuristic procedures in order to select a reduced number of various alternatives from which the investor can directly make a final decision.

Soft computingMathematical optimizationOrder (exchange)Computer scienceHeuristicPortfolioEfficient frontierSocial responsibilityMembership functionSelection (genetic algorithm)
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