Relevant bibliographies by topics / Storm sewers – Data processing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Storm sewers – Data processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Storm sewers – Data processing.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Storm sewers – Data processing"

1

Russo, Beniamino, David Sunyer, Marc Velasco, and Slobodan Djordjević. "Analysis of extreme flooding events through a calibrated 1D/2D coupled model: the case of Barcelona (Spain)." Journal of Hydroinformatics 17, no. 3 (2014): 473–91. http://dx.doi.org/10.2166/hydro.2014.063.

Full text
Abstract:
This paper presents the results of a calibrated 1D/2D coupled model simulating surface and sewer flows in Barcelona. The model covers 44 km2 of the city land involving 241 km of sewers. It was developed in order to assess the flood hazard in the Raval district, historically affected by flooding during heavy rainfalls. Special attention was paid to the hydraulic characterization of the inlet systems (representing the interface between surface and underground flows), through experimental expressions used to estimate the effective runoff flows into the sewers in case of storms. A 2D unstructured mesh with more than 400,000 cells was created on the basis of a detailed digital terrain model. The model was calibrated and validated using four sets of well-recorded flooding events that occurred in 2011. The aim of this paper is to show how a detailed 1D/2D coupled model can be adequately calibrated and validated using a wide set of sewer sensors and post-event collected data (videos, photos, emergency reports, etc.). Moreover, the created model presents significant computational time savings via parallel processing and hardware configuration. Considering the computational performances achieved, the model can be used for real-time strategies and as the core of early warning systems.
APA, Harvard, Vancouver, ISO, and other styles
2

Métadier, M., and J. L. Bertrand-Krajewski. "From mess to mass: a methodology for calculating storm event pollutant loads with their uncertainties, from continuous raw data time series." Water Science and Technology 63, no. 3 (2011): 369–76. http://dx.doi.org/10.2166/wst.2011.230.

Full text
Abstract:
With the increasing implementation of continuous monitoring of both discharge and water quality in sewer systems, large data bases are now available. In order to manage large amounts of data and calculate various variables and indicators of interest it is necessary to apply automated methods for data processing. This paper deals with the processing of short time step turbidity time series to estimate TSS (Total Suspended Solids) and COD (Chemical Oxygen Demand) event loads in sewer systems during storm events and their associated uncertainties. The following steps are described: (i) sensor calibration, (ii) estimation of data uncertainties, (iii) correction of raw data, (iv) data pre-validation tests, (v) final validation, and (vi) calculation of TSS and COD event loads and estimation of their uncertainties. These steps have been implemented in an integrated software tool. Examples of results are given for a set of 33 storm events monitored in a stormwater separate sewer system.
APA, Harvard, Vancouver, ISO, and other styles
3

Gong, N., X. Ding, T. Denoeux, J. L. Bertrand-Krajewski, and M. Clément. "Stormnet: a connectionist model for dynamic management of wastewater treatment plants during storm events." Water Science and Technology 33, no. 1 (1996): 247–56. http://dx.doi.org/10.2166/wst.1996.0024.

Full text
Abstract:
Models for solid transport in sewers during storm events are increasingly used. An important application of these models is the management of treatment plants during storm events so as to improve the quality of receiving waters. However, a major difficulty that prevents more general use of these tools is their calibration, which requires field data, accurate information about catchments and sewers, and a specific methodology. For that reason, a connectionist model called STORMNET has been designed to reproduce and replace usual conceptual and deterministic models. This model requires fewer data, can be automatically calibrated, and is comparatively simple. It is composed of two recurrent neural networks for the simulation of hydrographs and pollutographs of suspended solids, respectively. In this paper, we present an updated version of STORMNET designed for optimal management of wastewater treatment plants during storm events. This model has been validated using both model and real data. The results show the efficiency of STORMNET as a computational tool for simulating stormwater pollution.
APA, Harvard, Vancouver, ISO, and other styles
4

Schilperoort, Rémy, Holger Hoppe, Cornelis de Haan, and Jeroen Langeveld. "Searching for storm water inflows in foul sewers using fibre-optic distributed temperature sensing." Water Science and Technology 68, no. 8 (2013): 1723–30. http://dx.doi.org/10.2166/wst.2013.419.

Full text
Abstract:
A major drawback of separate sewer systems is the occurrence of illicit connections: unintended sewer cross-connections that connect foul water outlets from residential or industrial premises to the storm water system and/or storm water outlets to the foul sewer system. The amount of unwanted storm water in foul sewer systems can be significant, resulting in a number of detrimental effects on the performance of the wastewater system. Efficient removal of storm water inflows into foul sewers requires knowledge of the exact locations of the inflows. This paper presents the use of distributed temperature sensing (DTS) monitoring data to localize illicit storm water inflows into foul sewer systems. Data results from two monitoring campaigns in foul sewer systems in the Netherlands and Germany are presented. For both areas a number of storm water inflow locations can be derived from the data. Storm water inflow can only be detected as long as the temperature of this inflow differs from the in-sewer temperatures prior to the event. Also, the in-sewer propagation of storm and wastewater can be monitored, enabling a detailed view on advection.
APA, Harvard, Vancouver, ISO, and other styles
5

Gong, Ning, Thierry Denoeux, and Jean-Luc Bertrand-Krajewski. "Neural networks for solid transport modelling in sewer systems during storm events." Water Science and Technology 33, no. 9 (1996): 85–92. http://dx.doi.org/10.2166/wst.1996.0183.

Full text
Abstract:
Models for solid transport in sewers during storm events are increasingly used by engineers and operators to improve their systems and the quality of receiving waters. However, a major difficulty that prevents more general use of these models is their calibration, which requires field data, accurate information about catchments and sewers, and a specific methodology. Therefore, research has been carried out to assess the ability of connectionist models to reproduce and replace usual models for use by an operator. Such models require fewer data, are self-calibrated, and very easy to use. The first stage presented in this paper consists in a comparison between neural networks and the HYPOCRAS model, using simulations of real pollutographs for single storm events. Two specific recurrent neural networks based on the HYPOCRAS model and a general-purpose recurrent multilayer network are used to simulate hydrographs and pollutographs of TSS. The learning algorithm and the performance criterion used for optimization of these networks are described in detail. Experimental results with simulated and real data are then presented.
APA, Harvard, Vancouver, ISO, and other styles
6

Pan, Gang, Bao Wang, Shuai Guo, Wenming Zhang, and Stephen Edwini-Bonsu. "Statistical analysis of sewer odour based on 10-year complaint data." Water Science and Technology 81, no. 6 (2020): 1221–30. http://dx.doi.org/10.2166/wst.2020.217.

Full text
Abstract:
Abstract The City of Edmonton has been suffering from sewer odour problem for many years. Ten years of odour complaints data from 2008 to 2017 were statistically analyzed to identify major factors that relate to the odour problem. Spatial and temporal distributions of odour complaints in the city were first presented. Then relationships between the complaints and physical attributes of the sewer systems were analyzed by introducing a parameter of risk index. It was found that the snowmelt and storm events could possibly reduce odour complaints. Old sewer pipes and large drop structures are statistically more linked and thus significantly contribute to the complaints. The risk index relationship for three pipe materials is clay pipe > concrete pipe > PVC pipe. Combined sewers are more problematic in terms of odour complaints than sanitary sewers. And no clear correlation has been found between the changes of sewer pipe slope or angle and the complaints.
APA, Harvard, Vancouver, ISO, and other styles
7

Ruan, Mingchaun, and Jan B. M. Wiggers. "Application of time-series analysis to urban storm drainage." Water Science and Technology 36, no. 5 (1997): 125–31. http://dx.doi.org/10.2166/wst.1997.0180.

Full text
Abstract:
In urban storm drainage, deterministic models, such as SWMM, HydroWorks and MOUSE are commonly used. However, comprehensive research programmes, including field surveys, have indicated that most processes related to urban storm drainage have stochastic characteristic, like the occurrence of rainfall events, the processes of rainfall-runoff and flow routing in sewer networks3etc.. Particularly, sediments found in sewers either in suspension or in deposition, cannot be considered as having a unique entity. Inhomogeneity and randomness are just the nature of sewer sediment behaviour. Most data required for urban storm drainage are time-series data, such as rainfall intensity, water level measured in an outfall, CSO discharge and pollutant load etc.. Consequently, time-series analysis should be an alternative for predicting some relationships of urban storm drainage, such as (net) rainfall-CSO discharge, rainfall-water level and CSO discharge-pollutant load.
APA, Harvard, Vancouver, ISO, and other styles
8

Coghlan, Brian P., Richard M. Ashley, and George M. Smith. "Empirical equations for solids transport in combined sewers." Water Science and Technology 33, no. 9 (1996): 77–84. http://dx.doi.org/10.2166/wst.1996.0181.

Full text
Abstract:
An investigation of the transport of solids in combined sewers during both dry weather flow (DWF) periods and storms is described. The study was based on data obtained from a number of sites in the combined sewer system of Dundee, Scotland. The relationship between hydraulic conditions in a combined sewer and the transport of solids in suspension was examined. The aim was to arrive at a methodology by which an appropriate model could be selected or developed which would predict solids transport rates given information on hydraulic conditions. It was found that for individual sites, site-specific regression equations could be developed separately for dry weather and storm conditions. A non-site-specific regression equation was also developed, which was found to be preferable to the site specific equations, in terms of accuracy and ease of use. More important, however, were the fundamental procedures (ie the methodology) developed by which the model type was in each case selected and subsequently developed.
APA, Harvard, Vancouver, ISO, and other styles
9

Arthur, S., and R. M. Ashley. "The influence of near bed solids transport on first foul flush in combined sewers." Water Science and Technology 37, no. 1 (1998): 131–38. http://dx.doi.org/10.2166/wst.1998.0032.

Full text
Abstract:
The problems associated with deposited sediments in sewers, and their transport through sewer systems have been the subject of detailed fieldwork programmes in the UK, and elsewhere in Europe. Existing laboratory, and some field based research exercises have focused on the relatively small, discrete particles. It is clear, however, that combined sewer systems have inputs which comprise of a significant proportion of large organic solids (faecal and food wastes), as well as the finer range of particle sizes. The increased concern regarding CSO spills into the environment has fuelled the recent development of sewer flow quality models, such as HYDROWORKS QM and MOUSETRAP, some of which make no attempt to represent the transport of these larger organic particles. Herein, the results of a collaborative research programme undertaken between three UK universities and a water authority are discussed. Transport at the bed in sewers, as “near bed solids”, is defined. Based on a comprehensive data collection program undertaken in the Dundee combined sewerage system, a method is presented which may be used to estimate the rate of sediment transport near the bed in sewers. The influence that solids in transport near the bed have on first foul flush in combined sewers is discussed. A methodology is proposed which may be used to estimate the extent to which sediment in transport near the bed in sewers contributes to first foul flush phenomena, by describing the movement of a storm wave along a conceptual sewer length.
APA, Harvard, Vancouver, ISO, and other styles
10

Delleur, J. W., and Y. Gyasi-Agyei. "Prediction of Suspended Solids in Urban Sewers by Transfer Function Model." Water Science and Technology 29, no. 1-2 (1994): 171–79. http://dx.doi.org/10.2166/wst.1994.0663.

Full text
Abstract:
There is increasing concern about the sediments transported in urban storm sewers. Progress has been made on the measurement of suspended solids, and telemetry systems have been installed that permit remote access to flow, temperature and suspended solids concentration data. Using observations obtained in the main trunk sewer in Brussels, Belgium, a transfer function model for the prediction of suspended load concentration from temperature and discharge measurements was developed. This model is based on the transfer function methodology developed by Box and Jenkins. It is shown that the transfer function model correctly tracks the suspended solids observations and makes reasonable forecasts. It provides a valid alternative for the determination of suspended solids in urban sewers from discharge and water temperature observations which are more easily measurable on line than suspended solids.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Storm sewers – Data processing"

1

Nodine, Dewayne J. "Spatial decision support system for evaluation of land use plans based upon storm water runoff impacts : a theoretical framework." Virtual Press, 1996. http://liblink.bsu.edu/uhtbin/catkey/1020175.

Full text
Abstract:
All land uses affect storm water runoff However, different uses of the same site generate varying amounts of runoff Many communities have come to rely upon detention and/or retention basins for controlling the additional runoff resulting from land development. It is argued that this incremental approach to storm water management must be replaced with a more proactive long-term view.To achieve this, more user-friendly software capable of modeling the effect long-range land use plans have on the volume and behavior of storm water runoff is needed. This software, called a Spatial Decision Support System (SDSS), must be capable of guiding the user, who may not be an expert at runoff analysis, through the process and also capable of generating output in various formats understandable by lay persons. This study utilizes a systems analysis technique to develop a theoretical framework for the Storm Water SDSS.<br>Department of Urban Planning
APA, Harvard, Vancouver, ISO, and other styles
2

Elgendy, Mohamed Moustafa M. A. "Condition assessment and data integration for GIS-based storm water drainage infrastructure management systems." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2008. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Nyström, Simon, and Joakim Lönnegren. "Processing data sources with big data frameworks." Thesis, KTH, Data- och elektroteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188204.

Full text
Abstract:
Big data is a concept that is expanding rapidly. As more and more data is generatedand garnered, there is an increasing need for efficient solutions that can be utilized to process all this data in attempts to gain value from it. The purpose of this thesis is to find an efficient way to quickly process a large number of relatively small files. More specifically, the purpose is to test two frameworks that can be used for processing big data. The frameworks that are tested against each other are Apache NiFi and Apache Storm. A method is devised in order to, firstly, construct a data flow and secondly, construct a method for testing the performance and scalability of the frameworks running this data flow. The results reveal that Apache Storm is faster than Apache NiFi, at the sort of task that was tested. As the number of nodes included in the tests went up, the performance did not always do the same. This indicates that adding more nodes to a big data processing pipeline, does not always result in a better performing setup and that, sometimes, other measures must be made to heighten the performance.<br>Big data är ett koncept som växer snabbt. När mer och mer data genereras och samlas in finns det ett ökande behov av effektiva lösningar som kan användas föratt behandla all denna data, i försök att utvinna värde från den. Syftet med detta examensarbete är att hitta ett effektivt sätt att snabbt behandla ett stort antal filer, av relativt liten storlek. Mer specifikt så är det för att testa två ramverk som kan användas vid big data-behandling. De två ramverken som testas mot varandra är Apache NiFi och Apache Storm. En metod beskrivs för att, för det första, konstruera ett dataflöde och, för det andra, konstruera en metod för att testa prestandan och skalbarheten av de ramverk som kör dataflödet. Resultaten avslöjar att Apache Storm är snabbare än NiFi, på den typen av test som gjordes. När antalet noder som var med i testerna ökades, så ökade inte alltid prestandan. Detta visar att en ökning av antalet noder, i en big data-behandlingskedja, inte alltid leder till bättre prestanda och att det ibland krävs andra åtgärder för att öka prestandan.
APA, Harvard, Vancouver, ISO, and other styles
4

Tahiri, Ardit. "Online Stream Processing di Big Data su Apache Storm per Applicazioni di Instant Coupon." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10311/.

Full text
Abstract:
Big data è il termine usato per descrivere una raccolta di dati così estesa in termini di volume,velocità e varietà da richiedere tecnologie e metodi analitici specifici per l'estrazione di valori significativi. Molti sistemi sono sempre più costituiti e caratterizzati da enormi moli di dati da gestire,originati da sorgenti altamente eterogenee e con formati altamente differenziati,oltre a qualità dei dati estremamente eterogenei. Un altro requisito in questi sistemi potrebbe essere il fattore temporale: sempre più sistemi hanno bisogno di ricevere dati significativi dai Big Data il prima possibile,e sempre più spesso l’input da gestire è rappresentato da uno stream di informazioni continuo. In questo campo si inseriscono delle soluzioni specifiche per questi casi chiamati Online Stream Processing. L’obiettivo di questa tesi è di proporre un prototipo funzionante che elabori dati di Instant Coupon provenienti da diverse fonti con diversi formati e protocolli di informazioni e trasmissione e che memorizzi i dati elaborati in maniera efficiente per avere delle risposte in tempo reale. Le fonti di informazione possono essere di due tipologie: XMPP e Eddystone. Il sistema una volta ricevute le informazioni in ingresso, estrapola ed elabora codeste fino ad avere dati significativi che possono essere utilizzati da terze parti. Lo storage di questi dati è fatto su Apache Cassandra. Il problema più grosso che si è dovuto risolvere riguarda il fatto che Apache Storm non prevede il ribilanciamento delle risorse in maniera automatica, in questo caso specifico però la distribuzione dei clienti durante la giornata è molto varia e ricca di picchi. Il sistema interno di ribilanciamento sfrutta tecnologie innovative come le metriche e sulla base del throughput e della latenza esecutiva decide se aumentare/diminuire il numero di risorse o semplicemente non fare niente se le statistiche sono all’interno dei valori di soglia voluti.
APA, Harvard, Vancouver, ISO, and other styles
5

Addimando, Alessio. "Progettazione e prototipazione di un sistema di Data Stream Processing basato su Apache Storm." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10977/.

Full text
Abstract:
Con l’avvento di Internet, il numero di utenti con un effettivo accesso alla rete e la possibilità di condividere informazioni con tutto il mondo è, negli anni, in continua crescita. Con l’introduzione dei social media, in aggiunta, gli utenti sono portati a trasferire sul web una grande quantità di informazioni personali mettendoli a disposizione delle varie aziende. Inoltre, il mondo dell’Internet Of Things, grazie al quale i sensori e le macchine risultano essere agenti sulla rete, permette di avere, per ogni utente, un numero maggiore di dispositivi, direttamente collegati tra loro e alla rete globale. Proporzionalmente a questi fattori anche la mole di dati che vengono generati e immagazzinati sta aumentando in maniera vertiginosa dando luogo alla nascita di un nuovo concetto: i Big Data. Nasce, di conseguenza, la necessità di far ricorso a nuovi strumenti che possano sfruttare la potenza di calcolo oggi offerta dalle architetture più complesse che comprendono, sotto un unico sistema, un insieme di host utili per l’analisi. A tal merito, una quantità di dati così vasta, routine se si parla di Big Data, aggiunta ad una velocità di trasmissione e trasferimento altrettanto alta, rende la memorizzazione dei dati malagevole, tanto meno se le tecniche di storage risultano essere i tradizionali DBMS. Una soluzione relazionale classica, infatti, permetterebbe di processare dati solo su richiesta, producendo ritardi, significative latenze e inevitabile perdita di frazioni di dataset. Occorre, perciò, far ricorso a nuove tecnologie e strumenti consoni a esigenze diverse dalla classica analisi batch. In particolare, è stato preso in considerazione, come argomento di questa tesi, il Data Stream Processing progettando e prototipando un sistema bastato su Apache Storm scegliendo, come campo di applicazione, la cyber security.
APA, Harvard, Vancouver, ISO, and other styles
6

Al-Sinayyid, Ali. "JOB SCHEDULING FOR STREAMING APPLICATIONS IN HETEROGENEOUS DISTRIBUTED PROCESSING SYSTEMS." OpenSIUC, 2020. https://opensiuc.lib.siu.edu/dissertations/1868.

Full text
Abstract:
The colossal amounts of data generated daily are increasing exponentially at a never-before-seen pace. A variety of applications—including stock trading, banking systems, health-care, Internet of Things (IoT), and social media networks, among others—have created an unprecedented volume of real-time stream data estimated to reach billions of terabytes in the near future. As a result, we are currently living in the so-called Big Data era and witnessing a transition to the so-called IoT era. Enterprises and organizations are tackling the challenge of interpreting the enormous amount of raw data streams to achieve an improved understanding of data, and thus make efficient and well-informed decisions (i.e., data-driven decisions). Researchers have designed distributed data stream processing systems that can directly process data in near real-time. To extract valuable information from raw data streams, analysts need to create and implement data stream processing applications structured as a directed acyclic graphs (DAG). The infrastructure of distributed data stream processing systems, as well as the various requirements of stream applications, impose new challenges. Cluster heterogeneity in a distributed environment results in different cluster resources for task execution and data transmission, which make the optimal scheduling algorithms an NP-complete problem. Scheduling streaming applications plays a key role in optimizing system performance, particularly in maximizing the frame-rate, or how many instances of data sets can be processed per unit of time. The scheduling algorithm must consider data locality, resource heterogeneity, and communicational and computational latencies. The latencies associated with the bottleneck from computation or transmission need to be minimized when mapped to the heterogeneous and distributed cluster resources. Recent work on task scheduling for distributed data stream processing systems has a number of limitations. Most of the current schedulers are not designed to manage heterogeneous clusters. They also lack the ability to consider both task and machine characteristics in scheduling decisions. Furthermore, current default schedulers do not allow the user to control data locality aspects in application deployment.In this thesis, we investigate the problem of scheduling streaming applications on a heterogeneous cluster environment and develop the maximum throughput scheduler algorithm (MT-Scheduler) for streaming applications. The proposed algorithm uses a dynamic programming technique to efficiently map the application topology onto a heterogeneous distributed system based on computing and data transfer requirements, while also taking into account the capacity of underlying cluster resources. The proposed approach maximizes the system throughput by identifying and minimizing the time incurred at the computing/transfer bottleneck. The MT-Scheduler supports scheduling applications that are structured as a DAG, such as Amazon Timestream, Google Millwheel, and Twitter Heron. We conducted experiments using three Storm microbenchmark topologies in both simulated and real Apache Storm environments. To evaluate performance, we compared the proposed MT-Scheduler with the simulated round-robin and the default Storm scheduler algorithms. The results indicated that the MT-Scheduler outperforms the default round-robin approach in terms of both average system latency and throughput.
APA, Harvard, Vancouver, ISO, and other styles
7

Berni, Mila. "Inclusione di Apache Samza e Kafka nel framework RAM3S." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

Find full text
Abstract:
La rapida diffusione di dispositivi connessi ad Internet e il conseguente aumento della generazione di dati ha portato le piattaforme di data processing a voler sempre di più diminuire i tempi di latenza dell'elaborazione delle informazioni. Esistono vari framework dedicati al real-time processing, tutti con vari pro e contro, dipendenti anche dal tipo di applicazione che si vuole sviluppare. In particolare, il framework RAM3S si basa su Flink, Storm e Spark, tre piattaforme di Apache con caratteristiche differenti ma tutte aderenti al paradigma dello stream processing. Tramite RAM3S lo sviluppatore viene sgravato dall'impegno di dover conoscere approfonditamente i framework prima citati, mettendo a disposizione delle interfacce per semplificare lo sviluppo delle applicazioni. In questo lavoro di tesi verranno descritti i procedimenti per includere Apache Samza e Kafka all'interno di RAM3S. Samza è un framework per lo stream processing da affiancare a Flink, Storm e Spark mentre Kafka mantiene la coda di messaggi che, al momento, viene amministrata da RabbitMQ. Verranno inoltre svolte alcune analisi di prestazioni per valutare velocità e throughput del sistema in seguito ai cambiamenti prima citati.
APA, Harvard, Vancouver, ISO, and other styles

Books on the topic "Storm sewers – Data processing"

1

R, Dörring, Schilling Wolfgang, and International Association on Water Pollution Research and Control., eds. Real-time control of urban drainage systems: The state-of-the-art. IAWPRC, International Association on Water Pollution Research and Control, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Huber, Wayne Charles. The USEPA SWMM4 Stormwater Management Model: Version 4 user's manual. University of Guelph, School of Engineering, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Jim, Byrnes, and North Atlantic Treaty Organization. Scientific Affairs Division., eds. Computational noncommutative algebra and applications. Kluwer Academic Publishers, 2004.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Risley, John C. Effects of storm paths on precipitation chemistry, and variations of within-storm chemistry during selected storms in central Massachusetts, 1986-87. U.S. Dept. of the Interior, U.S. Geological Survey, 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Č, Maksimović, and Radojković M, eds. Urban drainage modelling: Proceedings of the International Symposium on Comparison of Urban Drainage Models with Real Catchment Data, UDM '86, Dubrovnik, Yugoslavia, 8-11 April 1986. Pergamon, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

(Editor), Jim Byrnes, and Gerald Ostheimer (Editor), eds. Computational Noncommutative Algebra and Applications: Proceedings of the NATO Advanced Study Institute, on Computatoinal Noncommutative Algebra and Applications, ... II: Mathematics, Physics and Chemistry). Springer, 2004.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Norbury, John, and Ian Roulstone. Invisible in the Storm: The Role of Mathematics in Understanding Weather. Princeton University Press, 2013.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Norbury, John, and Ian Roulstone. Invisible in the Storm: The Role of Mathematics in Understanding Weather. Princeton University Press, 2013.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

D, Farrar Paul, United States. Army. Corps of Engineers. Mobile District., U.S. Army Engineer Waterways Experiment Station., and Coastal Engineering Research Center (U.S.), eds. Storm impact assessment for beaches at Panama City, Florida. U.S. Army Engineer Waterways Experiment Station, 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Gupta, Saurabh, and Shilpi Saxena. Practical Real-time Data Processing and Analytics: Distributed Computing and Event Processing using Apache Spark, Flink, Storm, and Kafka. Packt Publishing - ebooks Account, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Storm sewers – Data processing"

1

Yadav, Vinit. "Real-Time Analytics with Storm." In Processing Big Data with Azure HDInsight. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2869-2_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Xu, Fang-Zhu, Zhi-Ying Jiang, Yan-Lin He, Ya-Jie Wang, and Qun-Xiong Zhu. "A Storm-Based Parallel Clustering Algorithm of Streaming Data." In Neural Information Processing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04212-7_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Deshai, N., S. Venkataramana, B. V. D. S. Sekhar, K. Srinivas, and G. P. Saradhi Varma. "A Study on Big Data Processing Frameworks: Spark and Storm." In Smart Intelligent Computing and Applications. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9690-9_43.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kombi, Roland Kotto, Nicolas Lumineau, Philippe Lamarre, Nicolo Rivetti, and Yann Busnel. "DABS-Storm: A Data-Aware Approach for Elastic Stream Processing." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-58664-8_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Zhang, Ziyu, Zitan Liu, Qingcai Jiang, Zheng Wu, Junshi Chen, and Hong An. "RDMA-Based Apache Storm for High-Performance Stream Data Processing." In Lecture Notes in Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79478-1_24.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Belikova, Marina Yurevna, and Alyona Viktorovna Glebova. "Cluster Analysis Algorithms for RS and WWLLN Data Processing." In Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1867-0.ch007.

Full text
Abstract:
Thunderstorm activity is indirectly taken into account when using statistics on forest fires. Another way is to use the data of the lightning discharge finding sensors. This chapter proposes using the data of the World Wide Lightning Location Network (WWLLN). To assess the probability of forest fire occurrence, it is necessary to know the energy and the spatial distribution of lightning discharges. For the analysis of the data of the storm-direction-finding WWLLN, it is proposed to use clustering algorithms. For the computational experiment, the region covering the Timiryazevskiy forestry of the Tomsk region (55.93 - 56.86) on the north, (83.94 - 85.07), and the data on lightning discharges registered by the WWLLN network in this region in July 2014. The sample data were 273 lightning discharges. The results of clustering are presented, as well as the image of the silhouette index for each object, the average value of the ASW index for grouping solutions obtained using the complete, kmeans, and dbscan algorithms.
APA, Harvard, Vancouver, ISO, and other styles
7

Vieira, Armando. "Business Applications of Deep Learning." In Natural Language Processing. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0951-7.ch023.

Full text
Abstract:
Deep Learning (DL) took Artificial Intelligence (AI) by storm and has infiltrated into business at an unprecedented rate. Access to vast amounts of data extensive computational power and a new wave of efficient learning algorithms, helped Artificial Neural Networks to achieve state-of-the-art results in almost all AI challenges. DL is the cornerstone technology behind products for image recognition and video annotation, voice recognition, personal assistants, automated translation and autonomous vehicles. DL works similarly to the brain by extracting high-level, complex abstractions from data in a hierarchical and discriminative or generative way. The implications of DL supported AI in business is tremendous, shaking to the foundations many industries. In this chapter, I present the most significant algorithms and applications, including Natural Language Processing (NLP), image and video processing and finance.
APA, Harvard, Vancouver, ISO, and other styles
8

Rashid, Mamoon, Harjeet Singh, Vishal Goyal, Nazir Ahmad, and Neeraj Mogla. "Efficient Big Data-Based Storage and Processing Model in Internet of Things for Improving Accuracy Fault Detection in Industrial Processes." In Security and Privacy Issues in Sensor Networks and IoT. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0373-7.ch009.

Full text
Abstract:
As the lot of data is getting generated and captured in Internet of Things (IoT)—based industrial devices which is real time and unstructured in nature. The IoT technology—based sensors are the effective solution for monitoring these industrial processes in an efficient way. However, the real—time data storage and its processing in IoT applications is still a big challenge. This chapter proposes a new big data pipeline solution for storing and processing IoT sensor data. The proposed big data processing platform uses Apache Flume for efficiently collecting and transferring large amounts of IoT data from Cloud—based server into Hadoop Distributed File System for storage of IoT—based sensor data. Apache Storm is to be used for processing this real—time data. Next, the authors propose the use of hybrid prediction model of Density-based spatial clustering of applications with noise (DBSCAN) to remove sensor data outliers and provide better accuracy fault detection in IoT Industrial processes by using Support Vector Machine (SVM) machine learning classification technique.
APA, Harvard, Vancouver, ISO, and other styles
9

Vieira, Armando. "Business Applications of Deep Learning." In Ubiquitous Machine Learning and Its Applications. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2545-5.ch003.

Full text
Abstract:
Deep Learning (DL) took Artificial Intelligence (AI) by storm and has infiltrated into business at an unprecedented rate. Access to vast amounts of data extensive computational power and a new wave of efficient learning algorithms, helped Artificial Neural Networks to achieve state-of-the-art results in almost all AI challenges. DL is the cornerstone technology behind products for image recognition and video annotation, voice recognition, personal assistants, automated translation and autonomous vehicles. DL works similarly to the brain by extracting high-level, complex abstractions from data in a hierarchical and discriminative or generative way. The implications of DL supported AI in business is tremendous, shaking to the foundations many industries. In this chapter, I present the most significant algorithms and applications, including Natural Language Processing (NLP), image and video processing and finance.
APA, Harvard, Vancouver, ISO, and other styles
10

Vieira, Armando. "Business Applications of Deep Learning." In Deep Learning and Neural Networks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch052.

Full text
Abstract:
Deep Learning (DL) took Artificial Intelligence (AI) by storm and has infiltrated into business at an unprecedented rate. Access to vast amounts of data extensive computational power and a new wave of efficient learning algorithms, helped Artificial Neural Networks to achieve state-of-the-art results in almost all AI challenges. DL is the cornerstone technology behind products for image recognition and video annotation, voice recognition, personal assistants, automated translation and autonomous vehicles. DL works similarly to the brain by extracting high-level, complex abstractions from data in a hierarchical and discriminative or generative way. The implications of DL supported AI in business is tremendous, shaking to the foundations many industries. In this chapter, I present the most significant algorithms and applications, including Natural Language Processing (NLP), image and video processing and finance.
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Storm sewers – Data processing"

1

Chen, Zhenhua, Jielong Xu, Jian Tang, Kevin Kwiat, and Charles Kamhoua. "G-Storm: GPU-enabled high-throughput online data processing in Storm." In 2015 IEEE International Conference on Big Data (Big Data). IEEE, 2015. http://dx.doi.org/10.1109/bigdata.2015.7363769.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Yang, Wenjie, Xingang Liu, Lan Zhang, and Laurence T. Yang. "Big Data Real-Time Processing Based on Storm." In 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2013. http://dx.doi.org/10.1109/trustcom.2013.247.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Zheng, Zhigang, Xin Zhang, and Tianhe Chi. "Visualizing Storm Surge Forecasting Data over the Web." In 2009 2nd International Congress on Image and Signal Processing (CISP). IEEE, 2009. http://dx.doi.org/10.1109/cisp.2009.5302305.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Banane, Mouad. "Real-Time Semantic Web Data Stream Processing Using Storm." In 2020 International Conference on Computing and Information Technology (ICCIT-1441). IEEE, 2020. http://dx.doi.org/10.1109/iccit-144147971.2020.9213720.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Guo, Shihang, and LiChen Zhang. "Railway Big Data Real-time Processing Based on Storm." In 2016 2nd Workshop on Advanced Research and Technology in Industry Applications (WARTIA-16). Atlantis Press, 2016. http://dx.doi.org/10.2991/wartia-16.2016.108.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Stojanovic, Dragan, Natalija Stojanovic, and Jovan Turanjanin. "Processing big trajectory and Twitter data streams using Apache STORM." In 2015 12th International Conference on Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS). IEEE, 2015. http://dx.doi.org/10.1109/telsks.2015.7357792.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Maske, Mohit M., and Prakash Prasad. "A real time processing and streaming of wireless network data using Storm." In 2015 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC). IEEE, 2015. http://dx.doi.org/10.1109/iccpeic.2015.7259471.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Dong, Wen, and Xin Zhang. "Research on WebGIS-Based Visualization of Storm Surge Disaster Based on Sphere - Take the Taiwan Strait Storm Surge Forecast Data as an Example." In 2009 2nd International Congress on Image and Signal Processing (CISP). IEEE, 2009. http://dx.doi.org/10.1109/cisp.2009.5305236.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Surekha, D., G. Swamy, and S. Venkatramaphanikumar. "Real time streaming data storage and processing using storm and analytics with Hive." In 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT). IEEE, 2016. http://dx.doi.org/10.1109/icaccct.2016.7831712.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Ye, Junyu, and Lichen Zhang. "The Big Data-Driven Industrial CPS Real-Time Processing System Based on Storm." In 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018). Atlantis Press, 2018. http://dx.doi.org/10.2991/ncce-18.2018.125.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Storm sewers – Data processing"

1

Butler, Afrachanna, Catherine Thomas, Nathan Beane, Anthony Bednar, and William Frederick. Phytomanagement of soil and groundwater at the Niagara Falls Storage Site (NFSS) using hybridized trees. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42083.

Full text
Abstract:
The Manhattan Engineer District previously used the 191-acre Niagara Falls Storage Site (NFSS) in Niagara County, New York, to store radioactive residues and wastes from uranium (U) ore processing. At present, management practices will determine whether enhanced evapotranspiration rates produced by hybridized shrub willow cuttings planted in 2016 will affect groundwater hydrology. Two shrub willow varieties were planted in an approximately one-half acre area to examine growth performance along a U impacted sanitary sewer line. Additionally, control plots will compare the effectiveness of shrub willows to unplanted areas. Observations of the planted area after 18 months showed success of shrub willow growth with increasing biomass. Chemical analysis from tree tissue samples of the field study showed no significant uptake of U or thorium (Th) to date. A greenhouse study conducted in parallel to the field study tested the willows under controlled greenhouse conditions and evaluated their ability to grow and accumulate contaminants under controlled conditions. Results from the greenhouse study demonstrated that U accumulation was minimal. Thus, this study demonstrates that the shrub willows are not accumulators of U or Th, an advantageous characteristic that implies stabilized contaminants in the soil and no translocation of U into the aboveground biomass.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Storm sewers – Data processing' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography