Neuro-fuzzy mid-term forecasting of electricity consumption using meteorological data

Abstract : Forecasting energy consumption is highly essential for strategic and operational planning. This study uses the Adaptive-Neuro-Fuzzy Inference System (ANFIS) for a mid-term forecast of electricity consumption. The model comprises of three meteorological variables as inputs and electricity consumption as output. Two ANFIS models with two clustering techniques (Fuzzy c-Means (FCM) and Grid Partitioning (GP) were developed (ANFIS-FCM and ANFIS- GP) to forecast monthly energy consumption based on meteorological variables. The performance of each model was determined using known statistical metrics. This compares the predicted electricity consumption with the observed and a statistical significance between the two reported. ANFIS-FCM model recorded a better mean absolute deviation (MAD), root mean square (RMSE), and mean absolute percentage error (MAPE) values of 0.396, 0.738, and 8.613 respectively compared to the ANFIS-GP model, which has MAD, RMSE, and MAPE values of 0.450, 0.762, and 9.430 values respectively. The study established that FCM is a good clustering technique in ANFIS compared to GP and recommended a comparison between the two techniques on hybrid ANFIS model

Assessment and Spatiotemporal Variation Analysis of Water Quality in the Zhangweinan River Basin, China

AbstractSpatiotemporal variation analysis of water quality and identification of water pollution sources in river basins is very important for water resources protection and sustainable utilization. In this study, fuzzy comprehensive analysis and two statistical methods including cluster analysis and seasonal Kendall test method were used to evaluate the spatiotemporal variation of water quality in the Zhangweinan River basin. The results for spatial cluster analysis and assessment on water quality at 19 monitoring sites indicated that water quality in the Zhangweinan River basin could be classified into two regions according to pollution levels. One is the Zhang River basin located in northwest of the Zhangweinan River basin where water quality is good. Another one includes the Wei River and eastern plain of the Zhangweinan River basin, and the water pollution in this region is serious, where the pollutants from point sources flow into the river and the water quality changes greatly. The results of temporal cluster analysis and seasonal Kendall test indicated that the sampling periods may be classified into three periods during 2002-2009 according to water quality. Results of temporal cluster analysis and seasonal Kendall test indicated that the study periods may be classified into three periods and two different trends was detected during the period of 2002-2009. The first period was the year of 2002-2003, during which water quality had deteriorated and serious pollution was observed in the Wei River basin and eastern plain of the Zhangweinan River basin. The second period was the year of 2004-2006, during which water quality became better. The year of 2007-2009 is the third period, during which water quality had been improved greatly. Despite that water quality in the Zhangweinan River basin had been improved during the period of 2004-2009, water quality in the Wei River (southwestern part of the basin), the Wei Canal River and the Zhangweixin River (eastern plain of the basin) is still poor. These results provide may useful information for better pollution control strategies in the Zhangweinan River basin

Anthropogenic alteration of the nitrogen cycle in coastal waters: Case studies from the Mediterranean Sea and the Gulf of Mexico

Tesis por compendio[ES] El nitrógeno (N) es uno de los elementos más importantes para la vida, pero el desequilibrio provocado sobre el ciclo del N está causando daños importantes a muchos ecosistemas en todo el mundo. En aguas costeras, los procesos del N se ven alterados por fertilizantes, la urbanización o la producción de energía. El objetivo principal de esta tesis es contribuir a la evaluación de cómo la actividad antropogénica y el cambio climático modifican la dinámica del N en aguas costeras. Con este propósito se seleccionaron dos lugares de estudio: la demarcación hidrográfica del Júcar (JRBD) en el Noroeste del Mar Mediterráneo y la Región Hidrológica del Golfo Central (CGHR) al Sur del Golfo de México. La tesis se presenta como una colección de cuatro artículos. El primer artículo evalúa cómo la nitrificación en aguas costeras es alterada por las presiones antropogénicas y en asentamientos urbanos en el JRBD. Mediante la aplicación de un modelo biogeoquímico simple que simula la dinámica del nitrito en nueve áreas costeras, se evaluó el desacoplamiento de los dos pasos de la nitrificación. Las conclusiones indican que las presiones antropogénicas modifican los picos de nitrito en invierno debido a las bajas temperaturas y que el segundo paso de la nitrificación es más sensible a la temperatura, lo que implica que el cambio climático puede contribuir al desacoplamiento. El segundo artículo evalúa las tendencias del nitrógeno inorgánico disuelto (NID) por el cambio climático en el JRBD. El efecto de las variables meteorológicas en las concentraciones de NID se estudió mediante la aplicación de redes neuronales artificiales simples entrenadas con datos de campo. Se observaron tendencias decrecientes de nitrito y nitrato a lo largo del siglo XXI bajo los escenarios climático RCP 4.5 y RCP 8.5, debido al aumento de las temperaturas y a la disminución de las precipitaciones, con cambios más significativos en invierno. El amonio no mostró ninguna tendencia anual significativa, pero se observaron aumentos o disminuciones durante algunos meses. En el tercer artículo se desarrolla un nuevo método basado en teoría de sistemas grises y entropía de Shannon para obtener información útil sobre la contaminación por N en áreas donde los datos disponibles son limitados. El método se aplicó a ocho estuarios del CGHR asociados a manglares. Se desarrollaron dos índices: el índice gris de prioridad de gestión de nitrógeno (GNMP) y el índice gris de presión de uso del suelo (GLUP). Ambos fueron comparados para validar la metodología y los resultados indican que la urbanización sobre playas y manglares es la principal causa de la contaminación de N. El cuarto artículo es un análisis espaciotemporal de la contaminación de N a lo largo de dos ríos que desembocan en una zona turística del CGHR asociada a manglares. Mediante técnicas estadísticas como el análisis de cluster, la prueba de MannKendall y la prueba W de MannWhitney, se realizó una evaluación del origen de la contaminación de N y las variaciones temporales de los compuestos de N. Los resultados concluyen que las concentraciones de N orgánico están aumentando a lo largo de la costa, y la principal fuente identificada fue la descomposición de la especie invasora de jacintos de agua en aguas salinas, que ha cubierto completamente las playas y manglares circundantes potenciado por la contaminación de N. El conjunto de la investigación concluye que tanto la contaminación como el cambio climático alteran el ciclo del N en aguas costeras al modificar elementos importantes del N como la nitrificación, las variaciones interanuales de las concentraciones de N o los ecosistemas costeros. Las diferencias en las características ecológicas y socioeconómicas de las dos zonas de estudio desempeñaron un papel decisivo en las presiones e impactos de las actividades antropogénicas. Además, los métodos desarrollados pueden aplicar[CAT] El nitrogen (N) és un dels elements més importants per a la vida, però el desequilibri provocat sobre el cicle del N està causant danys importants a molts ecosistemes. En aigües costaneres els processos del N es veuen alterats per fertilitzants, el desenvolupament urbà o la producció d'energia. L'objectiu principal d'aquesta investigació és contribuir a l'avaluació de com l'activitat antropogénica i el canvi climàtic modifiquen la dinàmica del N en aigües costaneres. Amb aquest propòsit es van seleccionar dos llocs d'estudi: la demarcació hidrogràfica del Xúquer (JRBD) al Nord-oest de la Mar Mediterrània i la Regió Hidrològica del Golf Central (CGHR) al Sud del Golf de Mèxic. La tesi es presenta com una col·lecció de quatre articles. El primer article avalua com la nitrificació en aigües costaneres es veu alterada per les pressions antropogèniques i prop dels assentaments urbans en el JRBD. Mitjançant l'aplicació d'un model biogeoquímic que simula la dinàmica del nitrit a nou àrees costaneres, es va avaluar el desacoblament dels dos passos de la nitrificació. Les conclusions indiquen que les pressions antropogèniques modifiquen els pics de nitrit observats a l'hivern a causa de les baixes temperaturas i que el segon pas de la nitrificació és més sensible a la temperatura, la qual cosa implica que el canvi climàtic pot contribuir al desacoblament d'aquests dos passos. El segon article avalua les tendències futures de nitrogen inorgànic dissolt (NID) pel canvi climàtic en el JRBD. L'efecte de les variables meteorològiques en les concentracions de NID es va estudiar mitjançant l'aplicació de xarxes neuronals artificials simples entrenades amb dades de camp. Es van observar tendències decreixents de nitrits i nitrats al llarg del segle XXI sota els escenaris climàtics RCP 4.5 i RCP 8.5, a causa de l'augment de les temperatures i a la disminució de les precipitacions, amb canvis més significatius a l'hivern. L'amoni no va mostrar cap tendència anual significativa, però es van observar augments o disminucions durant alguns mesos. En el tercer article es desenvolupa un nou mètode basat en la teoria dels sistemes grisos i l'entropia de Shannon per a obtindre informació útil sobre la contaminació per N en àrees on les dades disponibles són limitats. El mètode es va aplicar a huit estuaris del CGHR associats a manglars. Es van desenvolupar dos índexs: l'índex gris de prioritat de gestió de nitrogen (GNMP) i l'índex gris de pressió d'ús de la terra (GLUP). Els dos van ser comparats per a validar la metodologia. Els resultats indiquen que el desenvolupament urbà sobre platges i manglars és la principal causa de la contaminació de N en l'àrea d'estudi. El quart article és una anàlisi espacio-temporal de la contaminació de N al llarg de dues rius que desemboquen en una zona turística costanera del CGHR associada a manglars. Mitjançant tècniques estadístiques com l'anàlisi de clúster, les proves MannKendall i W de MannWhitney, es va realitzar una avaluació de l'origen de la contaminació de N i les variacions temporals dels compostos de N. Els resultats conclouen que les concentracions de N orgànic estan augmentant al llarg de la costa, i la principal font identificada va ser la descomposició de l'espècie invasora de jacints d'aigua en aigües salines, que ha cobert completament les platges i manglars circumdants potenciat per la contaminació de N. El conjunt de la investigació conclou que tant la contaminació com el canvi climàtic alteren el cicle del N en aigües costaneres en modificar els processos del N com la nitrificació, les variacions interanuals de les concentracions de N i la destrucció dels ecosistemes costaners. Les diferències en les característiques ecològiques i socioeconòmiques de les dues zones d'estudi van exercir un paper decisiu en les pressions i impactes de les activitats antropogèniques. A més, els mètodes desenvolupats poden[EN] Nitrogen (N) is one of the most important elements for life on Earth, but the unbalance caused to the N cylce is causing dramatic damage to many ecosystems around the world. In coastal waters, the N processes are altered by anthropogenic activities such as the excessive use of fertilizers, urban development or energy production. The main objective of this research is to contribute to the evaluation of how anthropogenic activities and climate change modify the N dynamics in coastal waters. For this purpose, two study sites were selected: the Jucar River Basin District (JRBD) in the Northwestern Mediterranean Sea (Spain) and the Central Gulf Hydrological Region (CGHR) in the Southern Gulf of Mexico (Mexico). The thesis is presented as a collection of four research articles. The first article evaluates how nitrification in coastal waters is altered by anthropogenic pressures and close to urban settlements in the JRBD. Through the application of a simple biogeochemical model that simulates nitrite dynamics to nine coastal areas, an evaluation of the decoupling of the two steps of nitrification was carried out. The main conclusions indicate that anthropogenic pressures modify the nitrite peaks observed in winter driven by low temperatures. The research also concludes that the second step of nitrification is more sensitive to temperature, which entails that climate change may contribute to the decoupling. The second article evaluates the future trends of dissolved inorganic nitrogen (DIN) concentrations under climate change in the JRBD. The effect of meteorological variables on DIN concentrations was studied through the application of simple artificial neural networks trained with field data. Decreasing trends of nitrite and nitrate concentrations were observed throughout the 21st century under both climatic scenarios RCP 4.5 and RCP 8.5, mainly due to rising temperatures and decreasing rainfall, with major changes expected in winter. On the other hand, ammonium did not show any significant annual trend but it either increased or decreased during some months. The third article develops a new method based on grey systems theory and Shannon entropy to derive useful information regarding N pollution in areas where only limited data is available. The method was applied to eight estuaries of the CGHR associated to mangroves. Two indexes were developed: the Grey Nitrogen Management Priority (GNMP) index and the Grey Land Use Pressure (GLUP) index. The two indexes were then confronted to validate the methodology. The results indicate that the urban development over beaches and mangroves is the leading cause of N pollution in the study area. The fourth article is a spatiotemporal analysis of N pollution along two rivers discharging into a touristic coastal area of the CGHR associated to mangroves. Through statistical techniques such as clustering analysis, the Mann-Kendall test and the Mann-Whitney W-test, an evaluation of the origine of N pollution and the temporal variations of the N compounds was performed. The results conclude than organic N concentrations are increasing along the coast, and the main potential source identified was the decomposition of the invasive species of water hyacinths in saline waters, which has completely covered the surrounding beaches and mangroves, enhanced by N pollution. Overall, the main conclusions are that both pollution and climate change alter the N cycle in coastal waters by modifying N processes such as nitrification, the interannual variations of N concentrations and by destroying the coastal ecosystems. The differences in ecological and socio-economic characteristics of the two study sites played a significant role in the pressures and impacts of anthropogenic activities. Moreover, the methods developed can be applied to other coastal regions to evaluate the anthropogenic alteration of the N cycle worldwide.This thesis was carried out with an international cotutelle between the Polytechnic University of Valencia in Spain and the Veracruzan University in Mexico. This thesis has been financed by the following scholarships: - Erasmus Mundus - MAYANET Grant Agreement Number 2014-0872/001 - 001, funded with support from the European Commission. - Cotutelle PhD scholarship granted by the Universitat Politècnica de València. - Excellence Scholarship awarded by the Mexican Government through the Mexican Agency for International Development Cooperation (AMEXCID)Temiño Boes, R. (2020). Anthropogenic alteration of the nitrogen cycle in coastal waters: Case studies from the Mediterranean Sea and the Gulf of Mexico [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/158560TESISCompendi

Extracting temporal patterns from smart city data

Mestrado de dupla diplomação com a DULAY UNIVERSITYIn the modern world data and information become a powerful instrument of management, business, safety, medicine and others. The most fashionable sciences are the sciences which allow us to extract valuable knowledge from big volumes of information. Novel data processing techniques remains a trend for the last five years, in a way that continues to provide interesting results. This paper investigates the algorithms and approaches for processing smart city data, in particular, water consumption data for the city of Bragança, Portugal. Data from the last seven years was processed according to a rigorous methodology, that includes five stages: cleaning, preparation, exploratory analysis, identification of patterns and critical interpretation of the results. After understanding the data and choosing the best algorithms, a web-based data visualizing tools was developed, providing dashboards to geospatial data representation, useful in the decision making of municipalities.В современном мире данные и информация стали одним из самых мощных инстру- ментов в управлении, бизнесе, безопасности, медицине, науке и социальной сфере. Са- мыми модными и востребованными науками в настоящий момент являются науки, поз- воляющие извлекать полезные знания из больших объемов информации. Новые методы обработки данных остаются тенденцией последних пяти лет и продолжают генерировать интересные результаты. В данной работе исследуются алгоритмы и подходы для обработ-ки данных "умного города", в частности, данных о потреблении воды в городе Браганса, Португалия. Данные за последние семь лет обрабатывались в соответствии со строгой методологией, включающей пять этапов: очистка, подготовка, исследовательский анализ, выявление закономерностей и критическая интерпретация результатов. Цель исследова-ниия - определение шаблонов поведения в потрблении воды связанных с определенными событиями и построение модели прогнозова на основе найденных закономерностей. В результате исчерпывающего анализа с помощью множества методов было установлено отсутствие систематических зависимостей в рассматриваемом типе данных. На заключи-тельном этапе был создан инструмент визуализации данных, обеспечивающий динами-ческие панели для представления аналитических данных о распределении потребления. Разработанный инструмент управления аналитикой полезен для принятия решений му-ниципалитетом

Use of Multispectral Aerial Videography for Jurisdictional Delineation of Wetland Areas

Multispectral aerial videography was used to reproduce the jurisdictional delineation of wetland area of approximately 50 hectares in Davis County, Utah Imagery from the system consisted of three-band composite with wavelengths covering 550 nm (±10 nm), 650 nm (±10 nm), and 850 nm (±10 nm). The site was overflown at three different flight dates during the 1992 growing season (June 2, July 22, October 1). Imagery resolution varied from 0.56 m to 0.81 m. Mosaiced images were analyzed with a Supervised clustering/maximum likelihood classifier, ISODATA clustering/Euclidan classifier, statistical clustering/maximum likelihood classifier, and fuzzy c-means clustering. Overall accuracies for wetland/upland designations as compared to ground truth data varied from 60% to 75%. The ISODATA method was the poorest performer for all dates and both of two accuracy testing techniques. Supervised clustering and statistical clustering were comparable with a slight edge in accuracy to the supervised clustering. The best all-round performer was the fuzzy c-means algorithm in terms of time spent and accuracy

Urban scene description for a multi scale classication of high resolution imagery case of Cape Town urban Scene

Includes abstract.Includes bibliographical references.In this paper, a multi level contextual classification approach of the City of Cape Town, South Africa is presented. The methodology developed to identify the different objects using the multi level contextual technique comprised three important phases

Objective analysis and ranking of Hungarian cities, with different classification techniques : part 1 : methodology

Összefoglalás - A tanulmány célja, hogy a magyarországi városokat és megyéket környezetminőségük és környezeti tudatosságuk szintje alapján osztályozza. Ahhoz, hogy ezt a feladatot megoldjuk, kiszámítottuk a „Green Cities Index", illetve a „Green Counties Index" értékeket, melyek alapján a városokat és a megyéket 7 különböző kategória 19 környezeti indikátora segítségével rangsoroltuk. Ezt követően azt a célt tűztük ki, hogy összehasonlítsuk a különböző clusterező eljárásokat a városok és megyék osztályozásában. Az SPSS szoftver segítségével elvégzett clusteranalízis mind a városokra, mind a megyékre 6-6 homogén csoportot eredményezett. Az R-nyelv segítségével végrehajtott clusteranalízis az agnes, a fanny és a pam algoritmusok felhasználásával történt. Summary - The aim of the study was to rank and classify Hungarian cities and counties according to their environmental quality and level of environmental awareness. To accomplish this task, „Green Cities Index" and „Green Counties Index" were calculated that rank cities and counties on the basis of seven different categories of 19 environmental indicators. Furthermore, our aim was to compare different methods in classifying cities and counties. Cluster analysis using SPSS software resulted in 6 homogenous groups for both the cities and the counties. Clustering with R-language was carried out using algorithms agnes, fanny and pam

Application of an adaptive neural fuzzy inference system to thermal comfort and group technology problems

AbstractThe Adaptive Neural Fuzzy Inference System (ANFIS) is used to design two vague systems, namely thermal comfort and group technologies in production and operations management. Results show that both systems can be modeled successfully by the combined use of a fuzzy approach and neural network learning

Stochastic techniques for the design of robust and efficient emission trading mechanisms

The assessment of greenhouse gases (GHGs) emitted to and removed from the atmosphere is highon both political and scientific agendas internationally. As increasing international concern and cooper- ation aim at policy-oriented solutions to the climate change problem, several issues have begun to arise regarding verification and compliance under both proposed and legislated schemes meant to reduce the human-induced global climate impact. The issues of concern are rooted in the level of confidence with which national emission assessments can be performed, as well as the management of uncertainty and its role in developing informed policy. The approaches to addressing uncertainty that was discussed at the 2nd International Workshop on Uncertainty in Greenhouse Gas Inventories 1 attempt to improve national inventories or to provide a basis for the standardization of inventory estimates to enable comparison of emissions and emission changes across countries. Some authors use detailed uncertainty analyses to enforce the current structure of the emissions trading system while others attempt to internalize high levels of uncertainty by tailoring the emissions trading market rules. In all approaches, uncertainty analysis is regarded as a key component of national GHG inventory analyses. This presentation will provide an overview of the topics that are discussed among scientists at the aforementioned workshop to support robust decision making. These range from achieving and report- ing GHG emission inventories at global, national and sub-national scales; to accounting for uncertainty of emissions and emission changes across these scales; to bottom-up versus top-down emission analy- ses; to detecting and analyzing emission changes vis-a-vis their underlying uncertainties; to reconciling short-term emission commitments and long-term concentration targets; to dealing with verification, com- pliance and emissions trading; to communicating, negotiating and effectively using uncertainty