Dissertations / Theses on the topic 'Aggregation Operator'

Disertacija je posvećena rešavanju jednačina distributivnosti gde nepoznate funkcije pripadaju nekim poznatim klasama operacija agregacije i primeni dobijenih rešenja u teoriji korisnosti. Dobijeni rezultati se generalno mogu podeliti u tri grupe. Prvu grupu čine rezultati iz Glave 2 dobijeni rešavanjem jednačina distributivnosti između GM-operacija agregacije i oslabljenih uninormi, GM-operacija agregacije i oslabljenih nulanormi, kao i GM-operacija agregacije i operacija agregacije bez neutralnog i absorbujućeg elementa. Druga grupa rezultata, takođe iz Glave 2, je dobijena rešavanjem jednačina uslovne (oslabljene) distributivnosi neprekidne nulanorme u odnosu na neprekidnu t-konormu, i neprekidne nulanonorme u odnosu na uninorme iz klasa U_min ∪U_max. Treća grupa rezultata (Glava 3) je proistekla iz primene dobijenih rezultata o uslovoj distributivnosti nulanorme u odnosu na t-konormu u teoriji korisnosti.
This dissertation is devoted to solving distributivity equations involving some well-known classes of aggregation operators, and application the obtained results to utility theory. In general, the obtained results can be divided into three groups. The first group are results from Chapter 2 obtained by solving distributivity equations between GM-aggregation operators and relaxed nullnorm, GM-aggregation operators and relaxed uninorms, as well as GM-aggregation operators and aggregation operators without neutral and absorbing element. The second group are results, also from Chapter 2, obtained by solving conditional (relaxed) distributivity of continuous nullnorm with respect to  continuous t-conorm, as well as continuous nullnorm with respect to uninorms from the classes U_min ∪ U_max. The third group are results (Chapter 3) arising from the application results on conditional distributivity of nullnorm with respect to t-conorm in utility theory.

Dans le cadre de la surveillance maritime, les opérationnels ont de plus en plus recours à l'imagerie radar pour classifier à grande distance un objet marin. Le traitement ISAR (Inverse Synthetic Aperture Radar) répond à ce besoin. Il repose en particulier sur l'analyse des mouvements propres de l'objet marin. Une fois l'objet détecté, il s'agit d'afficher sur la console tactique la représentation de la fréquence Doppler en fonction de la distance, aussi appelée image range-Doppler. Le travail présenté dans ce mémoire s'inscrit dans une perspective d'évolution opérationnelle de la chaîne de traitement existante. Il vise à produire de manière automatique la « meilleure » image range-Doppler. Dans cette thèse, nos contributions s'appuient sur l'idée de reconsidérer la chaîne de traitement en tenant compte de l'a priori que l'objet marin est un objet rigide dont la géométrie structure l'évolution du signal radar. Ainsi, dans une première contribution, nous proposons une nouvelle méthode d'analyse temps-fréquence du signal radar afin d'obtenir une image instantanée où l'opérationnel peut distinguer « au mieux » les superstructures de l'objet marin. Cette dernière est fondée sur la fusion de plusieurs représentations temps-fréquence issues de la classe de Cohen en faisant l'hypothèse que les composantes temps-fréquence sont des trajectoires structurées 2D dans le plan temps-fréquence, contrairement aux termes d'interférences induits par la propriété de bilinéarité des membres de cette classe. Une étude comparative sur données synthétiques et ISAR est menée pour confirmer la pertinence de notre approche, notamment du point de vue de la résolution temps-fréquence et de la suppression des termes d'interférences.Dans une seconde contribution, nous établissons une nouvelle procédure pour qualifier chaque image range-Doppler, obtenue à l'issue de l'analyse temps-fréquence, avec des mesures d'irrégularité de formes que nous fusionnons à l'aide d'un opérateur d'agrégation. Des simulations sur données réelles sont réalisées. Les résultats concordent avec une analyse subjective menée par des opérationnels, ce qui confirme l'efficacité de notre méthode
In maritime surveillance, radar imaging plays a key role to classify a maritime object. ISAR processing is one of the solutions, which takes advantage of the object rotational motion to provide a range-Doppler image.The work, presented in this report, is an evolution of the existing ISAR processing chain. Therefore, our contributions are based on the processing chain reconsideration by taking into account the fact that the maritime object is a rigid object, the geometry of which influences the radar signal evolution.In a first contribution, we propose a new time-frequency analysis method based on the aggregation of some time-frequency representations obtained with Cohen class members. It consists in differentiating the signal, assumed to be characterized by 2-D near-linear stable trajectories in the time-frequency plane, and the cross-terms, assumed to be geometrically unstructured. A comparative study is then carried out on ISAR synthetic data to confirm the efficiency of our approach.In a second contribution, we present a new procedure to characterize each range-Doppler image, obtained from a time-frequency analysis, by means of shape irregularity measures that are combined with a fuzzy logic operator. To validate our approach, simulations on real data are done. The results are compared to a subjective analysis carried out with practionners

The complexity of financial analysis, particularly on selection process or decision making problems, has increased rapidly over several decades. As a result, much attention has been focused on developing and implementing the efficient mathematical models for supporting this kind of problems. Multiple criteria decision analysis, an advanced field of operations research provides analysts or decision makers a broad range of methodologies, which are all suited to the complexity of financial decision analysis. In the financial modeling, uncertainty problems are inevitable, owing to the fact that the consequences of events are not precisely known. In addition, human judgments as part of analysis also contribute to it intricacy. Correspondingly, many studies have been concentrated on integrating uncertainty theories in modeling the real financial problems. One area of interest is on the inclusion of the element of human behavior or attitudinal character of decision makers. Aggregation operator in this case can offer a wide spectrum of analysis or flexibility in modeling the human behavior in financial decision analysis. In general, the main purpose of this work is on the study of financial selection problems from the perspective of decision analysis, uncertainty theories and aggregation operators. To be specific, the decision problems under a finite or discrete case and multidimensional factors are studied. The emphasis is given on the group decision making models, notably, the Dempster-Shafer theory (DST) of belief structure, the analytic hierarchy process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS). Moreover, the uncertainty theories based on fuzzy set theory and imprecise probability are employed, together with information fusion based on the ordered weighted average (OWA) operators. Quantitative and qualitative preferences, decision strategies based on the attitudinal character of decision makers, and majority concepts for group consensus are highlighted. The specific contributions of this work are summarized as the following: • The first contribution is on developing the multi-expert multi-criteria decision making (ME-MCDM) model with respect to two-stage aggregation processes. In specific, the aggregation of criteria is based on the integration of weighted arithmetic mean (WA) and OWA. The main attention is given on the proposed alternative OWAWA operator as an extension of immediate WA and OWAWA operators. Two approaches for modeling the majority opinion of experts are studied, in which based on the induced OWA (IOWA) operators. Some modifications to the support functions are suggested as to derive the order inducing variables. The analysis of ME-MCDM model based on these aggregation processes then is conducted. In this study the selection of investment strategy is used as to exemplify the model. • The weighted-selective aggregated majority-OWA operator may be considered as the second contribution. It is as an extension of the SAM-OWA operator, where the reliability of information sources is considered. The WSAM-OWA then is generalized to the quantified WSAM-OWA by incorporating the concept of linguistic quantifier, mainly for the group fusion strategy. The QWSAM-IOWA with an ordering step is proposed for the individual fusion strategy. These aggregation operators are then implemented to the case of alternative scheme of heterogeneous group decision analysis, in particular for a selection of investment problem. • Third contribution is represented by the development of linguistic group decision making with Dempster-Shafer belief structure. Different type of linguistic aggregation operator such as the 2-tuple induced linguistic OWA operator is suggested. Specifically, it is based on order-inducing variables in which the ordering of the arguments and uncertain situations can be assessed with linguistic information. Then, by using the 2-TILOWA in the D-S framework, the belief structure-2-TILOWA operator can be formed. Some of its main properties are studied. This model is applied in a selection of financial strategies. • The extension of AHP for group decision making model is given as the fourth contribution, notably, based on the inclusion of IOWA operators. Two-stage aggregation processes used in the AHP-GDM model are extended. Firstly, a generalization of weighted maximal entropy OWA under the IOWA operator is proposed as to aggregate the criteria. Further, the majority concept based on the IOWA and Minkowski OWA-based similarity measure is suggested to determine a consensus among experts. This model provides a variant of decision strategies for analyzing the individual and the majority of experts. The application in investment selection problem is presented to test the reliability of the model. • The fifth contribution is on the integration of heavy ordered weighted geometric (HOWG) aggregation operators in AHP-GDM model. In the sense of heavy OWA operator (HOWA), the heavy weighted geometric (HWG) and HOWG are introduced as extensions of the normal weighted geometric mean (WG) and the OWG by relaxing the constraints on the associated weighting vector. These HWG and HOWG operators then are utilized in the aggregation process of AHP-GDM, specifically on the aggregation of individual judgments procedure. The main advantage of the model, besides the complete overlapping of information such in classical methods, is that it can also accommodate partial and non-overlapping information in the formulation. An investment selection problem is applied to demonstrate the model. • The extension of TOPSIS for group decision making model by the inclusion of majority concept may be considered as the sixth contribution. The majority concept is derived based on the induced generalized OWA (IGOWA) operators. Two fusion schemes in TOPSIS model are designed. First, an external fusion scheme to aggregate the experts’ judgments with respect to the concept of majority opinion on each criterion is suggested. Then, an internal fusion scheme of ideal and anti-ideal solutions that represents the majority of experts is proposed using the Minkowski OWA distance measures. The comparison of the proposed model with some other TOPSIS models with respect to distance measures is presented. Here, a general case of selection problem is presented, specifically on the human resource selection problem. • Finally, the group decision making model based on conflicting bifuzzy sets (CBFS) is proposed. Precisely, the subjective judgments of experts, mainly from positive and negative aspects are considered simultaneously in the analysis. Moreover, the weighting method for the attribute (or sub-attribute) is subject to the integration of subjective and objective weights. The synthesis of CBFS in the model is naturally done by extending the fuzzy evaluation in parallel with the intuitionistic fuzzy set. A new technique to compute the similarity measure is proposed, in which, being the degree of agreement between the experts. The model then is applied in the case study of flood control project selection problem. To sum up, the presented thesis dealt with the extension of multi-criteria decision analysis models for the financial selection problems (as a specific scope) and also the general selection problems with the inclusion of attitudinal character, majority concept and fuzzy set theory. In particular, the group decision making model, Dempster-Shafer belief structure, AHP and TOPSIS are proposed to overcome the shortcoming of the existing models, i.e., related to the financial decision analysis. The applicability and robustness of the developed models have been demonstrated and some sensitivity analyses are also provided. The main advantages of the proposed models are to provide a more general and flexible models for a wider analysis of the decision problems.
La tesis, a través del análisis y desarrollo del Análisis de decisiones, Teorías de incertidumbre y Operadores de agregación, busca contribuir al estado del arte y nuevas propuesta de las necesidades y demandas que los decisores, responsables o e inversores financieros se encuentran por la creciente complejidad de sus análisis y estrategias, sobre todo en los procesos de selección o en los problemas de decisión. Así, el objetivo principal de esta tesis es el estudio de los problemas de selección financiera desde la perspectiva del análisis de decisiones, las teorías de la incertidumbre y los operadores de agregación. En concreto, se estudian los problemas de decisión en virtud de un conjunto finito de alternativas (caso discreto) y de factores multidimensionales. En el trabajo se desarrolla una extensión de los modelos de análisis de decisiones multicriterio y multiexperto que se utilizan en la resolución de los problemas de selección financiera (como ámbito específico), pero también en los problemas de selección generales, con la inclusión del carácter actitudinal, el concepto de mayoría y la teoría de los conjuntos borrosos. En particular, el énfasis se sitúa en los modelos de toma de decisiones en grupo y en la estructura de creencias Dempster-Shafer (D-S), el proceso analítico jerárquico (AHP) i la técnica de orden de preferencia por similitud con la solución ideal (TOPSIS). Además, se aplican las teorías de incertidumbre basadas en conjuntos borrosos y de probabilidades imprecisas juntamente con la fusión de la información basada en operadores OWA. También se destaca las preferencias cuantitativas y cualitativas, las estrategias de decisión basadas en el carácter actitudinal de los decisores, y el concepto de mayoría en el consenso grupal, de forma que se propone el desarrollo de operadores OWA, la generalización de los modelos AHP y TOPSIS, juntamente con el modelo de toma de decisiones grupal y la estructura de creencias Dempster-Shafer, con el fin de superar las deficiencias de los modelos existentes en relación con el análisis de decisiones financieras. En particular, la investigación realizada se puede sintetizar en siete aportaciones específicas al state-of-the-art del Análisis de decisiones y los operadores de agregación, con aplicaciones en diferentes problemas de decisión financiera: 1. Operadores de agregación basados en los OWA en los modelos de decisión Multiexpertos y Multicriterio. 2. Operadores ponderados SAM-OWA y su aplicación en modelos GDM con operadores lingüísticos. 3. Modelos GDM con operadores lingüísticos adaptados a la teoría de Dempster-Shafer con la aplicación de operadores de agregación inducidos lingüísticos. 4. Generalización del modelo AHP para decisiones grupales usando operadores OWA inducidos. 5. Introducción de operadores OWA geométricos y pesados en los modelos GDM y AHP. 6. Ampliación de los modelos TOPSIS con operadores de agregación basados en los OWA. 7. Desarrollo y aplicación del Conflicting bifuzzy a modelos de decisión MAGDM En la tesis se demuestra la aplicabilidad y la robustez de los modelos desarrollados, tanto con un esquema de agregación de expertos clásicos como con un esquema alternativo que separa por criterios de decisión. Las principales ventajas de los modelos propuestos son que se tratan modelos más generales y flexibles para un análisis más amplio de los problemas de decisión, en particular de los de selección financiera, que incorporen diversos criterios, expertos y componentes de incertidumbre y lingüísticos.

As finite element discretizations ever grow in size to address real-world problems, there is an increasing need for fast algorithms. Nowadays there are many GPU/CPU parallel approaches to solve such problems. Multigrid methods can be used to solve large-scale problems, or even better they can be used to precondition the conjugate gradient method, yielding better results in general. Capabilities of multigrid algorithms rely on the effectiveness of the inter-grid transfer operators. In this thesis we focus on the aggregation approach, discussing how different aggregation strategies affect the convergence rate. Based on these discussions, we propose an alternative parallel aggregation algorithm to improve convergence. We also provide numerous experimental results that compare different aggregation approaches, multigrid methods, and conjugate gradient iteration counts, showing that our proposed algorithm performs better in serial and parallel.
Modeling real-world problems incurs a high computational cost because these mathematical models involve large-scale data manipulation. Thus we need fast and efficient algorithms. Nowadays there are many high-performance approaches for these problems. One such method is called the Multigrid algorithm. This approach models a physical domain using a hierarchy of grids, and so the effectiveness of these approaches relies on how well data can be transferred from grid to grid. In this thesis, we focus on the aggregation approach, which clusters a grid’s vertices according to its connections. We also provide an alternative parallel aggregation algorithm to give a faster solution. We show numerous experimental results that compare different aggregation approaches and multigrid methods, showing that our proposed algorithm performs better in serial and parallel than other popular implementations.

Doktorska disertacija izučava primenu fazi operacija, prvenstveno agregacionih operatora na funkcije rastojanja i metrike. Originalan doprinos teze je u konstrukciji novih funkcija rastojanja i metrika primenom agregacionih operatora na neke polazne funkcije rastojanja i metrike. Za neke tipove agregacionih operatora i polaznih funkcija rastojanja i metrika su ispitane osobine ovako konstruisanih funkcija rastojanja i metrika. Za neke od njih su ispitane performanse pri primeni u segmentaciji slike „Fuzzy c-means“ algoritmom.
This thesis studies application of fuzzy operations, especially aggregation operators, on distance functions and metrics. The contribution of the thesis is construction of new distance functions and metrics by application of aggregation operators on some basic distance functions and metrics. For some types of aggregation operators and basic distance functions and metrics, properties of distance functions and metrics constructed in this way are analyzed. For some of them, performances in application in Fuzzy c-means algorithm are analyzed.

En el contexto actual, donde el calentamiento climático es cada vez más importante, existe la necesidad de limitar el consumo de combustibles fósiles. De esta manera, el transporte es uno de los sectores en los que más se están generando cambios en cuanto a la sostenibilidad. El vehículo eléctrico aparece como una solución para este cambio paulatino ya que no contamina localmente y su balance energético es muy eficiente. Así, se han propuesto diferentes programas para el crecimiento del vehículo eléctrico en el parque automotor. Sin embargo, el cambio de vehículos de gasolina por vehículos eléctricos genera desafíos en varios aspectos, como el impacto que ocasiona en la red eléctrica una implantación masiva: caídas de tensión, pérdidas de potencia, problemas con la calidad de la electricidad, inversiones importantes, etc. Se han planteado algunas soluciones en la parte operativa, pero muchas de ellas no han tomado en cuenta la flexibilidad de los usuarios, lo cual es muy importante para la adopción de vehículos eléctricos. De igual manera, en muchas ocasiones, en la literatura se asumen valores para ciertas variables (estado de carga, recorrido, tipo de batería, etc) que pueden cambiar según el comportamiento de cada usuario, lo que modificaría las previsiones realizadas. Finalmente, pocos trabajos han estudiado el impacto de lo vehículos eléctricos en redes eléctricas cuya gestión energética es más complicada debido a su aislamiento de una macrored y con alta penetración de energías renovables, como lo son las microredes. En este marco, esta tesis propone un enfoque novedoso en cuanto a la participación de los usuarios de vehículos eléctricos en la operación y planificación de diferentes sistemas eléctricos de potencia. Esta trata de algunos aspectos principales: disminución de costos de carga, participación en servicios de regulación, aprovechamiento de energía renovable, así como la planificación de generación de una microred incorporando vehículos eléctricos. En una primera parte, se presenta un análisis del vehículo eléctrico y su interacción en sistemas de potencia. De igual manera, se presentan los trabajos de investigación relacionados sobre la temática. En base al análisis de dichos trabajos, esta tesis propone una nueva metodología para optimizar la carga de los vehículos eléctricos. Se propone la participación de un nuevo agente del mercado eléctrico, el Agregador de vehículos eléctricos. Tendrá que gestionar la carga de dichos vehículos en una importante zona, coordinar con el operador de la red para evitar fallos y minimizar los costos de carga. De igual manera, se considera la diferente flexibilidad de los usuarios ya qu podrán escoger una tarifa que se adapte a su disponibilidad en espera y pagar el precio por aquello. La metodología ha sido aplicada a un caso de estudio a la red de Quito, Ecuador. Se propone también la participación en servicios de regulación, necesitando esta vez de usuarios que sean más flexibles al dejar su vehículo conectado a la red. Se considera las tarifas de la parte anterior para realizar dicho estudio. De igual manera, se aplicó al caso de estudio de la red de Quito, Ecuador. Con el crecimiento de las energías renovables, como solar y eólica, la gestión de la electricidad se vuelve más compleja. Con vistas a utilizar el exceso de energía renovable, se propone una tarifa de electricidad que permita al agregador de cargar los diferentes vehículos, tomando en cuenta precios bajos en periodos en donde la energía renovable esté en exceso. Finalmente, se plantea a planificación de generación de una microred que incluya la introducción masiva de vehículos eléctricos. Se aplicó al caso de las islas de Santa Cruz y Baltra, Galápagos, Ecuador, estudiando el impacto en los costos y en el medio ambiente de nueva generación y considerando la variación del precio del diésel debido a su incertidumbre.
In the current context, where global warming is growing progressively, it is fundamental to limit fossil fuels consumption. Hence, transportation is one of the sectors in which several changes are occurring considering the sustainability. The Electric Vehicle appears as a new solution for this gradual change; it does not pollute locally and its energy's balance is very efficient. So, different programs have been proposed for the growth of electric vehicles in the automotive market. Nevertheless, the change from internal combustion vehicles to electric vehicles generates challenges in several aspects, such as the impact in the electric grid of a massive introduction of electric vehicles: voltage drops, power losses, quality of electricity issues, important investments, among others. Several solutions in operation have been formulated, but most of them do not consider the flexibility of users, which is a significant criterion for the electric vehicle acquisition. Moreover, in several works of the literature, many variables are assumed (stateof- charge, routes, type of battery, etc), which can vary significantly depending on the user, so also the results. Finally, few works have studied the impact of electric vehicles in very complex power systems, as the ones that are isolated from a macrogrid and because of significant penetration of renewable energy sources, such as microgrids. In this context, this thesis proposes a novel approach to the participation of the electric vehicle users in operation and planning of different electric power systems. This thesis is intended to cover various topics: charging costs decrease, regulation services participation, use of an excess of renewable energy, and the power generation planning of a microgrid considering the introduction of electric vehicles. In a first part, an analysis of the electric vehicle and its interaction with power systems is presented. Additionally, the principal works on the topic are summarized. Based on the analysis of these works, this thesis proposes a new methodology for optimizing the charge of electric vehicles. The participation of a new agent of the electricity market, the electric vehicle aggregator, is proposed. It has the ability to manage the charge of the electric vehicles in a zone with significant size, to coordinate with the grid operator in order to avoid troubles and to minimize charging costs. Furthermore, the different flexibility of electric vehicle users is considered because they will choose an EV customer choice product (CCP) that is adapted to their waiting needs and to the cost they can pay. The methodology has been applied to a case study in the grid of Quito, Ecuador. The participation in regulation services has been also considered to discuss this participation in Ancillary services. The CCPs from the part before are considered for performing such study but assuming more involvement from the electric vehicle users. The case study of Quito, Ecuador, was also studied. With the growth of renewable energies, such as solar and wind, the electricity management becomes more complicated. In order to use the excess of renewable energy, an EV charging mechanism for the aggregator is proposed, based on low prices when the renewable energy is in excess. Finally, a power generation planning for a microgrid is proposed, considering the massive introduction of electric vehicles. The case of the Santa Cruz and Baltra islands, Galapagos, Ecuador are studied to determine its costs and environmental impacts, based on diesel costs sensitivity studies to account for its uncertainty.
En el context actual, on l'escalfament climàtic és cada vegada més important, hi ha la necessitat de limitar el consum de combustibles fòssils. El transport és un dels sectors en els quals més s'estan generant canvis pel que fa a la sostenibilitat. El vehicle elèctric apareix com una solució per a aquest canvi gradual ja que no contamina localment i el seu balanç energètic és molt eficient. Així, s'han proposat diferents programes per al creixement del vehicle elèctric al parc automotor. No obstant això, el canvi de vehicles de gasolina per vehicles elèctrics generen desafiaments en diversos aspectes, com son l'impacte que ocasiona a la xarxa elèctrica una implantació massiva: caigudes de tensió, pèrdues de potència, problemes amb la qualitat de l'electricitat, inversions importants, disminució de la vida útil dels transformadors, etc. S'han plantejat algunes solucions a la part operativa, però moltes d'elles no han tingut en compte la flexibilitat dels usuaris, la qual cosa és molt important per a l'adopció de vehicles elèctrics. De la mateixa manera, en moltes ocasions, en la literatura s'assumeixen valors per certes variables (estat de càrrega, recorregut, tipus de bateria, etc.) que poden canviar segons el comportament de cada usuari, el que modificaria les previsions realitzades. Finalment indicar que pocs treballs han estudiat l'impacte del que vehicles elèctrics en xarxes elèctriques on la gestió energètica és més complicada a causa del seu aïllament d'una macroxarxa i amb alta penetració d'energies renovables, com ho són les microxarxes. En aquest marc, aquesta tesi proposa un enfocament nou pel que fa a la participació dels usuaris de vehicles elèctrics en l'operació i planificació de diferents sistemes elèctrics de potència. Aquesta tracta alguns aspectes principals: disminució de costos de càrrega, participació en serveis de regulació, aprofitament d'energia renovable, així com la planificació de generació d'una microxarxa incorporant vehicles elèctrics. En una primera part, es presenta una anàlisi del vehicle elèctric i la seva interacció en sistemes de potència. De la mateixa manera, es presenten els treballs de recerca relacionats sobre la temàtica. En base a l'anàlisi d'aquests treballs, aquesta tesi proposa una nova metodologia per optimitzar la càrrega dels vehicles elèctrics. Es proposa la participació d'un nou agent del mercat elèctric, el Agregador de vehicles elèctrics. Haurà de gestionar la càrrega d'aquests vehicles en una important zona, coordinar amb l'operador de la xarxa per evitar fallades i minimitzar els costos de càrrega. De la mateixa manera es considera la diferent flexibilitat dels usuaris ja que podran escollir una tarifa que s'adapti a la seva disponibilitat en espera i pagar el preu per allò. La metodologia ha estat aplicat a un cas d'estudi a la xarxa de Quito, Equador. Es proposa també la participació en serveis de regulació, necessitant aquest cop d'usuaris que siguin més flexibles en deixar el seu vehicle connectat a la xarxa. Es consideren les tarifes de la part anterior per a realitzar dit estudi. De la mateixa manera, es va aplicar al cas d'estudi de la xarxa de Quito, Equador. Amb el creixement de les energies renovables, com solar i eòlica, la gestió de l'electricitat es torna més complexa. Amb vista a utilitzar l'excés d'energia renovable, es proposa un tarifa d'electricitat que permeti a l'agregador de carregar els diferents vehicles, especialment en períodes on l'energia renovable estigui en excés. Finalment, es planteja la planificació de generació d'una microxarxa que inclogui la introducció massiva de vehicles elèctrics. En concret, es va aplicar al cas de la illes de Santa Cruz i Baltra, Galápagos, Equador, estudiant l'impacte de la nova generació en els costos i en el medi ambient i considerant la variació del preu del dièsel, causa de la seva incertesa.
Clairand Gómez, JM. (2018). New strategies for the massive introduction of electric vehicles in the operation and planning of Smart Power Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/110971
TESIS

Electrical energy is one of the most common forms of energy these days. Consequently, electric power system is an indispensable part of any society. However, due to the deregulation of electricity markets and the growth in the share of power generation by uncontrollable renewable energies such as wind and solar, power system simulations are more challenging than earlier. Thus, new techniques for simplifying these simulations are needed. One important example of such simplification techniques is the power system reduction. Power system reduction can be used at least for four different purposes: a) Simplifying the power system simulations, b) Reducing the computational complexity, c) Compensating the data unavailability, and d) Reducing the existing uncertainty. Due to such reasons, power system reduction is an important and necessary subject, but a challenging task to do. Power system reduction is even more essential when system operators are facing very large-scale power systems and when the renewable energy resources like hydro, wind, and solar have a high share in power generation. This thesis focuses on the topic of large-scale power system reduction with high penetration of renewable energy resources and tries to pursue the following goals: • The thesis first reviews the different methods which can be used for simplifying the power system studies, including the power system reduction. A comparison among three important simplification techniques is also performed to reveal which simplification results in less error and more simulation time decrement. • Secondly, different steps and methods for power system reduction, including network aggregation and generation aggregation, are introduced, described and discussed. • Some improvements regarding the subject of power system reduction, i.e. on both network aggregation and generation aggregation, are developed. • Finally, power system reduction is applied to some power system problems and the results of these applications are evaluated. A general conclusion is that using power system simplification techniques and specially the system reduction can provides many important advantages in studying large-scale power systems with high share of renewable energy generations. In most of applications, not only the power system reduction highly reduces the complexity of the power system study under consideration, but it also results in small errors. Therefore, it can be used as an efficient method for dealing with current bulk power systems with huge amounts of renewable and distributed generations.

The Doctoral Degrees issued upon completion of the programme are issued by Comillas Pontifical University, Delft University of Technology and KTH Royal Institute of Technology. The invested degrees are official in Spain, the Netherlands and Sweden, respectively. QC 20150116

碩士
國立臺東大學
理工學院綠色科技產業碩士專班
102
This study mainly discusses key service innovation factors for those tourist hotels at Taitung area, and the service innovation evaluation model based on the fuzzy aggregation operator will be made in this study. Besides, the key factors mined from the customers and the employee can be also used to make the necessary discussion. The obtained results can applied to those tourist hotels managers for making the subsequent planning about their service innovation. The primary findings will be given as follows: (1) According to the staff’s viewpoints: The attitude of service providers had viewed as the most important consideration from the dimension of the novelty in delivering flow. And, setting the business strategy will be the important item from the service adjustment. Developing the innovation service will be recognized as the important item from the novelty about the service to markets. Finally, imporving the current service will be viewed as the important item from the novelty about the service to enterprises. (2) According to the customers’ viewpoints: the rsult reveals that the attitude of service providers had viewed as the most important consideration from the dimension of the novelty in delivering flow. And, it is the same with the viewpoint of staff. And, setting the business strategy will be regarded as the important item from the dimension about service adjustment. Besides, the issue of the affection about the new service to markets will be recognized as the important item for the novelty about service to markets. Finally, imporving the current services will be viewed as the important item for the novelty about service to enterprises.

碩士
國立臺灣科技大學
資訊工程系
103
Multiple attribute decision making and multiple attribute group decision making based on interval-valued intuitionistic fuzzy sets are important research topic. In this thesis, we propose a new multiple attribute decision making method based on the proposed interval-valued intuitionistic fuzzy geometric averaging operators. First, we propose the interval-valued intuitionistic fuzzy weighted geometric averaging (IVIFWGA) operator, the interval-valued intuitionistic fuzzy ordered weighted geometric averaging (IVIFOWGA) operator and the interval-valued intuitionistic fuzzy hybrid geometric averaging (IVIFHGA) operator based on the proposed multiplication operator between interval-valued intuitionistic fuzzy values and the proposed power operator of an interval-valued intuitionistic fuzzy value. Based on the proposed IVIFWGA operator, IVIFOWGA operator and the IVIFHGA operator, we also propose a new method for multiple attribute decision making. The experimental results show that the proposed multiple attribute decision making method can overcome the drawbacks of the existing multiple attribute decision making methods. It provides us with a useful way for multiple attribute decision making in interval-valued intuitionistic fuzzy environments. Moreover, we propose the interval-valued intuitionistic fuzzy weighted averaging (IVIFWA) operator, the interval-valued intuitionistic fuzzy ordered weighted averaging (IVIFOWA) operator and the interval-valued intuitionistic fuzzy hybrid averaging (IVIFHA) operator based on the proposed addition operator between interval-valued intuitionistic fuzzy values. Based on the proposed IVIFWA operator, IVIFOWA operator and the IVIFHA operator, we also propose a new method for multiple attribute group decision making. The experimental results show that the proposed multiple attribute group decision making method can overcome the drawbacks of the existing methods. It provides us with a useful way for multiple attribute group decision making in interval-valued intuitionistic fuzzy environments.

Tese de Doutoramento em Ciências e Tecnologias da Informação apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra
Machine-to-Machine (M2M) is an emerging paradigm that rapidly has gained ground in the scenario of modern wireless communications. In recent years, companies have started to introduce numerous products and services for machine-to-machine communication, and it is still expected that M2M will enable the connectivity of millions of devices. The central idea of this paradigm is to provide a pervasive presence of machines and make them share data cooperatively to take decisions with low human intervention. In this context, group communication is present in M2M as a type of communication frequently required, since the number of devices is expected to be large. However, the complexity, the heterogeneity, the large scale, and vast types of scenarios turn efficient machine-to-machine group communication into a major challenge. Tackling this challenge, this thesis in the first part proposes mechanisms, usually classified as in-network data aggregation, to improve machine-to-machine group communication by allowing the member nodes of a M2M group to eliminate data redundancy and to reduce overhead caused by transmissions of small payloads. Additionally to the proposed in-network data aggregation, this thesis presents tree-based heuristics and also formulates a mathematical model to compute the maximum network lifetime. It also discusses a performance comparison between the proposed heuristics and the optimal solution, highlighting the pros and cons of each approach. Furthermore, this thesis describes a set of experiments using real devices to test the feasibility of the proposals and measure the performance of the improvements in a group communication scenario. The second part of this thesis addresses the problem of energy efficiency of nodes with capabilities to harvest energy from the ambient. Regarding this problem, two mechanisms that apply data aggregation procedures are proposed. In both cases, the applied data aggregation procedures are used to regulate the amount of traffic flowing over the paths. The ultimate objective of this traffic regulation is to control the energy consumption of the nodes in order to achieve neutral operation or energy sustainability. The condition to be in neutral operation is to keep the remaining energy of a node away from maximum and minimum. The first mechanism uses the residual energy as parameter to determine the amount of data that should be aggregated before the transmission. The second mechanism exploits the fact that there is a bottleneck in terms of residual energy in the path towards the gateway. This bottleneck is the node with minimum energy reserve in the path. So, the enhanced mechanism exchanges messages to find the critical node which is causing the bottleneck and aggregates the traffic to maintain the critical node in neutral operation. This mechanism is implemented in a real embedded system and adapts and extends some of the M2M standard protocols. The benefits and drawbacks of the contributions have been demonstrated using different evaluation methods, such as simulations, mathematical models, and real experimentation. Furthermore, the evaluations have been conducted with well-known metrics and the results show that all the proposed mechanisms were able to outperform related proposals in literature.
Máquina para máquina(M2M) é um paradigma emergente que rapidamente ganhou terreno no cenário das comunicações sem fio modernas. Nos últimos anos, as empresas começaram a introduzir inúmeros produtos e serviços para a comunicação M2M, e ainda é esperado que M2M permita a conectividade de milhares e milhões de dispositivos. A idéia central desse paradigma é fornecer presença pervasiva de dispositivos e fazê-los compartilhar dados de forma cooperativa para tomar decisões com baixa intervenção humana. Neste contexto, a comunicação em grupo está presente em M2M como um tipo de comunicação frequentemente necessária, uma vez que se espera que o número de dispositivos seja grande. No entanto, a complexidade, a heterogeneidade, a grande escala e os vastos tipos de cenários transformam a comunicação eficiente de grupos M2M em um grande desafio. Enfrentando este desafio, na primeira parte desta tese é proposto procedimentos para melhorar a comunicação em grupo M2M, permitindo que o nó membro de um grupo M2M elimine a redundância de dados e reduza o overhead causado por transmissões de pequenos payloads. Adicionalmente aos procedimentos propostos, esta tese apresenta heurísticas baseadas em árvore e também formula um modelo matemático para calcular o tempo de vida máximo da rede. Uma comparação de desempenho entre as heurísticas propostas e a solução ótima também é discutida, destacando-se os prós e contras de cada abordagem. Além disso, esta tese descreve um conjunto de experimentos usando dispositivos reais que testam a viabilidade e medem o desempenho das melhorias propostas em um cenário de comunicação em grupo. A segunda parte da tese aborda o problema da eficiência energética de nós com capacidade de extrair energia do ambiente. Em relação a este problema, dois mecanismos que aplicam agregação de dados são propostos. Em ambos casos, os procedimentos de agregação de dados são usados para regular a quantidade de tráfego que fluem pelos caminhos. O objetivo final de regular o tráfego é controlar o consumo de energia dos nós a fim de alcançar operação neutra ou sustentabilidade energética. A condição para estar em operação neutra significa manter a energia residual da reserva dentro um intervalo longe do máximo e mínimo. O primeiro mecanismo proposto com esse fim usa a energia residual como parâmetro para determinar a quantidade de dados que deve ser agregada antes da transmissão. O segundo mecanismo explora o facto que existe um gargalo em termos de energia residual no caminho em direção ao gateway. Esse gargalo é o nó com reserva mínima de energia no caminho. Assim, o mecanismo aprimorado troca mensagens para encontrar nó crítico que o gargalo de energia no caminho e agrega o tráfego para manter o nó crítico em operação neutra. Este mecanismo foi implementado em um sistema embarcado real, adapta e estende alguns protocolos padrões de M2M. Os benefícios e desvantagens das contribuições foram demonstrados usando diferentes métodos de avaliação, tais como simulações, modelos matemáticos e experimentação real. Além disso, as avaliações foram realizadas com métricas bem conhecidas e os resultados mostram que todos os mecanismos propostos foram capazes de superar propostas relacionadas da literatura.
Brazilian National Counsel of Technological and Scientific Development (CNPq) under the grant 246599/2012-0

Το πρόβλημα της βελτιστοποίησης ερωτημάτων πολλαπλών κριτηρίων σε βάσεις δεδομένων είναι ένα αρκετά δύσκολο και ενδιαφέρον ερευνητικά πρόβλημα, διότι χαρακτηρίζεται από αντικρουόμενες απαιτήσεις. Κάθε βήμα στην απάντηση ενός ερωτήματος μπορεί να εκτελεστεί με παραπάνω από έναν τρόπους. Για την επίλυση τέτοιου είδους ερωτημάτων έχουν προταθεί διάφοροι αλγόριθμοι, με πιο πρόσφατους τους: Mariposa, M' και Generate Partitions. Ο Mariposa και ο Μ' εφαρμόζονται στην βάση δεδομένων Mariposa, η οποία δίνει την δυνατότητα στον χρήστη να καθορίζει την επιθυμητή εξισορόπηση (tradeoff) καθυστέρησης/κόστους για κάθε ερώτημα που θέτει. Ο αλγόριθμος Mariposa ακολουθεί μία προσέγγιση απληστίας (greedy approach) προσπαθώντας σε κάθε βήμα να μεγιστοποιήσει το «κέρδος» ενώ ο Μ' χρησιμοποιεί σύνολα βέτιστων κατά Pareto λύσεων για την επιλογή του επόμενου βήματος στην θέση του κριτηρίου απληστίας. Τέλος, ο αλγόριθμος Generate Partition χρησιμοποιεί έναν διαχωρισμό του χώρου απαντήσεων χρησιμοποιώντας δομές R-trees πετυχαίνοντας πολύ καλή απόδοση.
The optimization of queries in distributed database systems is known to be subject to delicate trade-offs. For example, the Mariposa database system allows users to specify a desired delay-cost tradeoff (that is to supply a decreasing function u(d) specifying how much the user is willing to pay in order to receive the query results within time d) Mariposa divides a query graph into orizontal strides analyzes each stride, and uses a greedy heuristic to find the best plan for all strides.

Dissertação de Mestrado Integrado em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia
Redes de Internet das Coisas consistem numa rede física de objetos, veículos e prédios, dotados de tecnologia capaz de realizar transferência de dados. A maioria dos dispositivos de Internet das Coisas são alimentados energeticamente por uma bateria, por isso, o consumo de energia é um aspeto crítico que precisa de ser controlado e resolvido. Este trabalho visa contribuir para a eficiência energética no contexto de Internet das Coisas, com foco na energia proveniente de “Harvesting”, que representa a energia possível de recuperar do meio ambiente.Assim, estas redes são compostas por dispositivos com capacidade para extrair energia do meio ambiente, prolongando a sua vida útil no que concerne à bateria. Do mesmo modo, são capazes de realizar operações de uma forma mais recorrente e complexa, incluindo a captura de dados do meio ambiente e a transmissão destes entre vários dispositivos da rede. Neste tipo de sistemas, o objetivo é atingir um “estado operacional perpétuo”, alcançado através de mecanismos que apoiam a Operação Energética Neutra. A criação destas redes é um dos desafios atuais. Deste modo, é importante garantir o equilíbrio geral da utilidade da rede de acordo com os recursos energéticos que as operações requerem.Por conseguinte, para gerir o nível de energia de modo a evitar que as baterias esgotem a sua capacidade, o que provoca perda de dados, podemos desenvolver e aplicar diferentes soluções que contribuem para uma melhoria da eficiência energética. Alguns dos referidos trabalhos estudam a melhor periocidade para a recolha e transferência de dados de acordo com a topologia da rede. Outros, por sua vez, analisam a implementação da deteção de eventos e de mecanismos de agregação de dados. Para contribuir para a resolução deste problema analisámos um modelo teórico, com uma topologia de múltiplas etapas baseada em Programação Linear Inteira Mista que visava uma rede de Operação Energética Otimizada, considerando uma aquisição forçada de ocorrências espaço-temporais notáveis e um sistema com parâmetros configuráveis, que podiam ser especificados de acordo com o propósito da rede. Contudo, este sistema continha limitações de desempenho e de adaptação a cenários mais realistas. Assim, nesta dissertação, foi desenvolvida uma heurística especialmente concebida para superar as limitações de desempenho do modelo ótimo analisado.O sistema para a heurística foi desenvolvido e testado com recurso ao software ‘Cooja’, que permite a criação de uma rede de sensores de alto nível e que integra as respetivas comunicações. Um dos principais objetivos foi aperfeiçoar a solução obtida pelo modelo ótimo analisado, através de métodos que permitem a simulação de topologias de redes com um maior número de sensores. As ferramentas utilizadas concedem realismo ao sistema, pois aproximam o comportamento previsto do modelo à realidade que nos rodeia, fazendo com que o sistema fique pronto para uma implementação no mundo real, em especial nas características das tecnologias e protocolos de comunicação. Os resultados experimentais obtidos confirmam e validam os resultados do modelo teórico, permitindo a formulação de uma heurística distribuída no tempo real que considera todos os pontos já mencionados. Para além disto, a heurística permite ao utilizador definir todas as funcionalidades da rede sem comprometer o funcionamento da operação energética neutra.
The Internet of Things consists of a physical network that interconnects objects, vehicles, buildings, and all things that have communication capabilities. Many of the devices in the Internet of Things are battery powered and thus energy consumption becomes a critical aspect that needs to be tackled. This work aims to contribute to the energy efficiency within the Internet of Things context, with the focus on Energy Harvesting Internet of Things Networks.These networks comprise devices that can extract energy from the environment and thus prolong the battery lifetime, while being able to perform more frequent and complex operations, including sensing the environment and transmitting the collected data. In such systems, the goal of having a “perpetual operational state” can be achieved through mechanisms that support Energy Neutral Operation. Creating a network that keeps the Energy Neutral Operation is a challenging task because it is crucial to ensure an overall network utility balance, according to the energy resources that the network operation requires. Therefore, managing the energy level to avoid losing data and deplete the batteries can be achieved considering different features such as rate of data collection, event detection, data transfer and aggregation mechanisms, and network topology. To address this issue, this thesis has analyzed a multi-hop model that uses an enforced acquisition of spatiotemporal notable occurrences and configurable parameters, which can be specified according to the purpose of the network. It is based on a Mixed-Integer Linear Program approach in order to achieve an optimal operation of the Energy Harvesting IoT Network. As this model has limitations in performance and adaptation to more realistic scenarios, in this thesis, an heuristic was conceived to overcome the performance limitations of the optimal model. The complete system for the heuristic was developed and tested using the' Cooja' software, which allows the creation of a sensor network at a high level while embedding its communication capabilities. One of the main objectives was to improve the solution obtained through methods that allow networks with many sensors to use realistic tools that approach the model's behavior to reality. The experimental results confirm and validate the mentioned theoretical model, allowing the formulation of a distributed heuristic in real-time that considers all the points already mentioned. Beyond this, the developed heuristic enables the user to define all the network's functionalities without compromising the energy neutral operation.
Outro - This project is supported by the European Regional Development Fund (FEDER), through the Competitiveness and Internationalization Operational Programme (COMPETE 2020) of the Portugal 2020 framework, and Financial Support National Public (FCT)(OE); Project, MOBIWISE, POCI-01-0145-FEDER-016426; The work performed in this dissertation was realized within the scope of the MobiWise project: From mobile sensing to mobility advising (P2020 SAICTPAC/0011/2015), co-financed by national funds through the FCT - Foundation for Science and Technology, I.P., within the scope of the project CISUC - UID/CEC/00326/2020 and by European Social Fund, through the Regional Operational Program Centro 2020.