Estimation of a probability in inverse binomial sampling under normalized linear-linear and inverse-linear loss

Sequential estimation of the success probability $p$ in inverse binomial sampling is considered in this paper. For any estimator $\hatvap$, its quality is measured by the risk associated with normalized loss functions of linear-linear or inverse-linear form. These functions are possibly asymmetric, with arbitrary slope parameters $a$ and $b$ for $\hatvap < p$ and $\hatvap > p$ respectively. Interest in these functions is motivated by their significance and potential uses, which are briefly discussed. Estimators are given for which the risk has an asymptotic value as $p \rightarrow 0$, and which guarantee that, for any $p \in (0,1)$, the risk is lower than its asymptotic value. This allows selecting the required number of successes, $\nnum$, to meet a prescribed quality irrespective of the unknown $p$. In addition, the proposed estimators are shown to be approximately minimax when $a/b$ does not deviate too much from $1$, and asymptotically minimax as $\nnum \rightarrow \infty$ when $a=b$.

Spatial Estimation of Sub-Hour Global Horizontal Irradiance Based on Official Observations and Remote Sensors.

This study was motivated by the need to improve densification of Global Horizontal Irradiance (GHI) observations, increasing the number of surface weather stations that observe it, using sensors with a sub-hour periodicity and examining the methods of spatial GHI estimation (by interpolation) with that periodicity in other locations. The aim of the present research project is to analyze the goodness of 15-minute GHI spatial estimations for five methods in the territory of Spain (three geo-statistical interpolation methods, one deterministic method and the HelioSat2 method, which is based on satellite images). The research concludes that, when the work area has adequate station density, the best method for estimating GHI every 15 min is Regression Kriging interpolation using GHI estimated from satellite images as one of the input variables. On the contrary, when station density is low, the best method is estimating GHI directly from satellite images. A comparison between the GHI observed by volunteer stations and the estimation model applied concludes that 67% of the volunteer stations analyzed present values within the margin of error (average of +-2 standard deviations).

Estimation of nitrogen budgets for contrasting catchments at the landscape scale.

A comprehensive assessment of nitrogen (N) flows at the landscape scale is fundamental to understand spatial interactions in the N cascade and to inform the development of locally optimised N management strategies. To explore these interactions, complete N budgets were estimated for two contrasting hydrological catchments (dominated by agricultural grassland vs. semi-natural peat-dominated moorland), forming part of an intensively studied landscape in southern Scotland. Local scale atmospheric dispersion modelling and detailed farm and field inventories provided high resolution estimations of input fluxes. Direct agricultural inputs (i.e. grazing excreta, N2 fixation, organic and synthetic fertiliser) accounted for most of the catchment N inputs, representing 82% in the grassland and 62% in the moorland catchment, while atmospheric deposition made a significant contribution, particularly in the moorland catchment, contributing 38% of the N inputs. The estimated catchment N budgets highlighted areas of key uncertainty, particularly N2 exchange and stream N export. The resulting N balances suggest that the study catchments have a limited capacity to store N within soils, vegetation and groundwater. The "catchment N retention", i.e. the amount of N which is either stored within the catchment or lost through atmospheric emissions, was estimated to be 13% of the net anthropogenic input in the moorland and 61% in the grassland catchment. These values contrast with regional scale estimates: Catchment retentions of net anthropogenic input estimated within Europe at the regional scale range from 50% to 90%, with an average of 82% (Billen et al., 2011). This study emphasises the need for detailed budget analyses to identify the N status of European landscapes.

Estimation of spanish bunkering at EU level of secas

On December 17 came into force on community standard marine fuels.The SOx emissions will be increased in the main shipping routes at a rate of 3 to 4% annually. Most of the sulphur burden will be attributed to shipping activity. Therefore the extension of SECAs could be beneficial towards the improvement of air quality. This paper begins with a review of the current situation SECAS and ECAS areas, highlighting the rules to be implemented shortly. The aim of the paper is known the current situation bunkering determine the estimated short term in Spain from economic variables

Estimation of modal parameters in structures using multiple time history records

In Operational Modal Analysis of structures we often have multiple time history records of vibrations measured at different time instants. This work presents a procedure for estimating the modal parameters of the structure processing all the records, that is, using all available information to obtain a single estimate of the modal parameters. The method uses Maximum Likelihood Estimation and the Expectation Maximization algorithm. Finally, it has been applied to various problems for both simulated and real structures and the results show the advantage of the joint analysis proposed.

Joint statistical analysis of multiple measurement setups for the estimation of vibrational modes

Computing the modal parameters of large structures in Operational Modal Analysis often requires to process data from multiple non simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors that are fixed for all the measurements, while the other sensors are moved from one setup to the next. One possibility is to process the setups separately what result in different modal parameter estimates for each setup. Then the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global modes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a state space model that can be used to process all setups at once so the global mode shapes are obtained automatically and subsequently only a value for the natural frequency and damping ratio of each mode is computed. We also present how this model can be estimated using maximum likelihood and the Expectation Maximization algorithm. We apply this technique to real data measured at a footbridge.

Desing and development of a robotic platform for the evaluation of search algorithms

Plant diseases represent a major economic and environmental problem in agriculture and forestry. Upon infection, a plant develops symptoms that affect different parts of the plant causing a significant agronomic impact. As many such diseases spread in time over the whole crop, a system for early disease detection can aid to mitigate the losses produced by the plant diseases and can further prevent their spread [1]. In recent years, several mathematical algorithms of search have been proposed [2,3] that could be used as a non-invasive, fast, reliable and cost-effective methods to localize in space infectious focus by detecting changes in the profile of volatile organic compounds. Tracking scents and locating odor sources is a major challenge in robotics, on one hand because odour plumes consists of non-uniform intermittent odour patches dispersed by the wind and on the other hand because of the lack of precise and reliable odour sensors. Notwithstanding, we have develop a simple robotic platform to study the robustness and effectiveness of different search algorithms [4], with respect to specific problems to be found in their further application in agriculture, namely errors committed in the motion and sensing and to the existence of spatial constraints due to land topology or the presence of obstacles.

Interval-based ranking in noisy evolutionary multiobjective optimization

As one of the most competitive approaches to multi-objective optimization, evolutionary algorithms have been shown to obtain very good results for many realworld multi-objective problems. One of the issues that can affect the performance of these algorithms is the uncertainty in the quality of the solutions which is usually represented with the noise in the objective values. Therefore, handling noisy objectives in evolutionary multi-objective optimization algorithms becomes very important and is gaining more attention in recent years. In this paper we present ?-degree Pareto dominance relation for ordering the solutions in multi-objective optimization when the values of the objective functions are given as intervals. Based on this dominance relation, we propose an adaptation of the non-dominated sorting algorithm for ranking the solutions. This ranking method is then used in a standardmulti-objective evolutionary algorithm and a recently proposed novel multi-objective estimation of distribution algorithm based on joint variable-objective probabilistic modeling, and applied to a set of multi-objective problems with different levels of independent noise. The experimental results show that the use of the proposed method for solution ranking allows to approximate Pareto sets which are considerably better than those obtained when using the dominance probability-based ranking method, which is one of the main methods for noise handling in multi-objective optimization.

Using damage from 2010 Haiti earthquake for vulnerability estimation of typical structures in Port-au-Prince (Haiti).

After the 2010 Haiti earthquake, that hits the city of Port-au-Prince, capital city of Haiti, a multidisciplinary working group of specialists (seismologist, geologists, engineers and architects) from different Spanish Universities and also from Haiti, joined effort under the SISMO-HAITI project (financed by the Universidad Politecnica de Madrid), with an objective: Evaluation of seismic hazard and risk in Haiti and its application to the seismic design, urban planning, emergency and resource management. In this paper, as a first step for a structural damage estimation of future earthquakes in the country, a calibration of damage functions has been carried out by means of a two-stage procedure. After compiling a database with observed damage in the city after the earthquake, the exposure model (building stock) has been classified and through an iteratively two-step calibration process, a specific set of damage functions for the country has been proposed. Additionally, Next Generation Attenuation Models (NGA) and Vs30 models have been analysed to choose the most appropriate for the seismic risk estimation in the city. Finally in a next paper, these functions will be used to estimate a seismic risk scenario for a future earthquake.

Computación evolutiva de bosques de expansión mínimos con restricción de grado y de rol

Encontrar el árbol de expansión mínimo con restricción de grado de un grafo (DCMST por sus siglas en inglés) es un problema NP-complejo ampliamente estudiado. Una de sus aplicaciones más importantes es el dise~no de redes. Aquí nosotros tratamos una nueva variante del problema DCMST, que consiste en encontrar el árbol de expansión mínimo no solo con restricciones de grado, sino también con restricciones de rol (DRCMST), es decir, a~nadimos restricciones para restringir el rol que los nodos tienen en el árbol. Estos roles pueden ser nodo raíz, nodo intermedio o nodo hoja. Por otra parte, no limitamos el número de nodos raíz a uno, por lo que, en general, construiremos bosques de DRCMSTs. El modelado en los problemas de dise~no de redes puede beneficiarse de la posibilidad de generar más de un árbol y determinar el rol de los nodos en la red. Proponemos una nueva representación basada en permutaciones para codificar los bosques de DRCMSTs. En esta nueva representación, una permutación codifica simultáneamente todos los árboles que se construirán. Nosotros simulamos una amplia variedad de problemas DRCMST que optimizamos utilizando ocho algoritmos de computación evolutiva diferentes que codifican los individuos de la población utilizando la representación propuesta. Los algoritmos que utilizamos son: algoritmo de estimación de distribuciones (EDA), algoritmo genético generacional (gGA), algoritmo genético de estado estacionario (ssGA), estrategia evolutiva basada en la matriz de covarianzas (CMAES), evolución diferencial (DE), estrategia evolutiva elitista (ElitistES), estrategia evolutiva no elitista (NonElitistES) y optimización por enjambre de partículas (PSO). Los mejores resultados fueron para el algoritmo de estimación de distribuciones utilizado y ambos tipos de algoritmos genéticos, aunque los algoritmos genéticos fueron significativamente más rápidos.---ABSTRACT---Finding the degree-constrained minimum spanning tree (DCMST) of a graph is a widely studied NP-hard problem. One of its most important applications is network design. Here we deal with a new variant of the DCMST problem, which consists of finding not only the degree- but also the role-constrained minimum spanning tree (DRCMST), i.e., we add constraints to restrict the role of the nodes in the tree to root, intermediate or leaf node. Furthermore, we do not limit the number of root nodes to one, thereby, generally, building a forest of DRCMSTs. The modeling of network design problems can benefit from the possibility of generating more than one tree and determining the role of the nodes in the network. We propose a novel permutation-based representation to encode the forest of DRCMSTs. In this new representation, one permutation simultaneously encodes all the trees to be built. We simulate a wide variety of DRCMST problems which we optimize using eight diferent evolutionary computation algorithms encoding individuals of the population using the proposed representation. The algorithms we use are: estimation of distribution algorithm (EDA), generational genetic algorithm (gGA), steady-state genetic algorithm (ssGA), covariance matrix adaptation evolution strategy (CMAES), diferential evolution (DE), elitist evolution strategy (ElististES), non-elitist evolution strategy (NonElististES) and particle swarm optimization (PSO). The best results are for the estimation of distribution algorithm and both types of genetic algorithms, although the genetic algorithms are significantly faster. iv

Contributions to uncertainty reduction in the estimation of PV plants performance

Esta tesis doctoral presenta un procedimiento integral de control de calidad en centrales fotovoltaicas, que comprende desde la fase inicial de estimación de las expectativas de producción hasta la vigilancia del funcionamiento de la instalación una vez en operación, y que permite reducir la incertidumbre asociada su comportamiento y aumentar su fiabilidad a largo plazo, optimizando su funcionamiento. La coyuntura de la tecnología fotovoltaica ha evolucionado enormemente en los últimos años, haciendo que las centrales fotovoltaicas sean capaces de producir energía a unos precios totalmente competitivos en relación con otras fuentes de energía. Esto hace que aumente la exigencia sobre el funcionamiento y la fiabilidad de estas instalaciones. Para cumplir con dicha exigencia, es necesaria la adecuación de los procedimientos de control de calidad aplicados, así como el desarrollo de nuevos métodos que deriven en un conocimiento más completo del estado de las centrales, y que permitan mantener la vigilancia sobre las mismas a lo largo del tiempo. Además, los ajustados márgenes de explotación actuales requieren que durante la fase de diseño se disponga de métodos de estimación de la producción que comporten la menor incertidumbre posible. La propuesta de control de calidad presentada en este trabajo parte de protocolos anteriores orientados a la fase de puesta en marcha de una instalación fotovoltaica, y las complementa con métodos aplicables a la fase de operación, prestando especial atención a los principales problemas que aparecen en las centrales a lo largo de su vida útil (puntos calientes, impacto de la suciedad, envejecimiento…). Además, incorpora un protocolo de vigilancia y análisis del funcionamiento de las instalaciones a partir de sus datos de monitorización, que incluye desde la comprobación de la validez de los propios datos registrados hasta la detección y el diagnóstico de fallos, y que permite un conocimiento automatizado y detallado de las plantas. Dicho procedimiento está orientado a facilitar las tareas de operación y mantenimiento, de manera que se garantice una alta disponibilidad de funcionamiento de la instalación. De vuelta a la fase inicial de cálculo de las expectativas de producción, se utilizan los datos registrados en las centrales para llevar a cabo una mejora de los métodos de estimación de la radiación, que es la componente que más incertidumbre añade al proceso de modelado. El desarrollo y la aplicación de este procedimiento de control de calidad se han llevado a cabo en 39 grandes centrales fotovoltaicas, que totalizan una potencia de 250 MW, distribuidas por varios países de Europa y América Latina. ABSTRACT This thesis presents a comprehensive quality control procedure to be applied in photovoltaic plants, which covers from the initial phase of energy production estimation to the monitoring of the installation performance, once it is in operation. This protocol allows reducing the uncertainty associated to the photovoltaic plants behaviour and increases their long term reliability, therefore optimizing their performance. The situation of photovoltaic technology has drastically evolved in recent years, making photovoltaic plants capable of producing energy at fully competitive prices, in relation to other energy sources. This fact increases the requirements on the performance and reliability of these facilities. To meet this demand, it is necessary to adapt the quality control procedures and to develop new methods able to provide a more complete knowledge of the state of health of the plants, and able to maintain surveillance on them over time. In addition, the current meagre margins in which these installations operate require procedures capable of estimating energy production with the lower possible uncertainty during the design phase. The quality control procedure presented in this work starts from previous protocols oriented to the commissioning phase of a photovoltaic system, and complete them with procedures for the operation phase, paying particular attention to the major problems that arise in photovoltaic plants during their lifetime (hot spots, dust impact, ageing...). It also incorporates a protocol to control and analyse the installation performance directly from its monitoring data, which comprises from checking the validity of the recorded data itself to the detection and diagnosis of failures, and which allows an automated and detailed knowledge of the PV plant performance that can be oriented to facilitate the operation and maintenance of the installation, so as to ensure a high operation availability of the system. Back to the initial stage of calculating production expectations, the data recorded in the photovoltaic plants is used to improved methods for estimating the incident irradiation, which is the component that adds more uncertainty to the modelling process. The development and implementation of the presented quality control procedure has been carried out in 39 large photovoltaic plants, with a total power of 250 MW, located in different European and Latin-American countries.

Application of self-organizing techniques for the distribution of heterogeneous multi-tasks in multi-robot systems

This paper focuses on the general problem of coordinating of multi-robot systems, more specifically, it addresses the self-election of heterogeneous and specialized tasks by autonomous robots. In this regard, it has proposed experimenting with two different techniques based chiefly on selforganization and emergence biologically inspired, by applying response threshold models as well as ant colony optimization. Under this approach it can speak of multi-tasks selection instead of multi-tasks allocation, that means, as the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. It has evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.