Bibliographies thématiques / Evaluation of energy consumption

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Littérature scientifique sur le sujet « Evaluation of energy consumption »

Auteur : Grafiati
Publié le 4 juin 2021
Mis à jour le 30 mai 2022

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Articles de revues sur le sujet "Evaluation of energy consumption"

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Li, Nan, Jing Zhao et Neng Zhu. « Building Energy Consumption Prediction Evaluation Model ». Advanced Materials Research 280 (juillet 2011) : 101–5. http://dx.doi.org/10.4028/www.scientific.net/amr.280.101.

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Building energy consumption prediction provides the possibility for regulating running condition of equipments in advance. Then the equipments will keep good movement and building energy consumption will reduce obviously. This paper built an energy consumption prediction evaluation model according to Matlab Artificial Neural Network Toolbox. The model was trained and simulated by operation data in June-September of 2008 and 2009 of a case building. Then it can be used to predict this building energy consumption by special data, such as meteorological characteristics of prediction year, operation load, operation time and energy consumption of last year. With more building samples, the model will be used in wide range of building energy consumption prediction.
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Zhao, Liang, Ruobing Liang, Jili Zhang, Liangdong Ma et Tianyi Zhao. « A new method for building energy consumption statistics evaluation : ratio of real energy consumption expense to energy consumption ». Energy Systems 5, no 4 (25 décembre 2013) : 627–42. http://dx.doi.org/10.1007/s12667-013-0111-3.

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Mu, Tian, Geng Geng, Chongjie Wang et Ran Zou. « Evaluation approach of terminal energy consumption of public buildings based on a standardized model ». Indoor and Built Environment 31, no 4 (14 février 2022) : 1066–78. http://dx.doi.org/10.1177/1420326x211054429.

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The influencing degree of different factors on terminal energy consumption of public building varies distinctly. If the actual measured terminal energy consumption is directly analyzed, the comparison basis is often inconsistent, which may lead to errors of results. In order to evaluate the energy consumption based on a unified standard, eliminating the interference of influencing factors, the standardization and revision of the measurement value of the terminal energy consumption is necessary. By considering domestic public building samples of different climate regions as research objects, this research has introduced a dimensionality reduction and integration method for evaluating influencing factors that could affect the terminal energy consumption of public buildings based on principal component and clustering analysis. Then, the quantitative mathematical expressions of the relationship between terminal energy consumptions and influencing factors were established through multiple linear regression fitting, formulating the standardized mathematical model of the terminal energy consumption of public buildings. According to the energy consumption standardized model, the evaluation approach was provided and scored based on mode analysis method. This approach can evaluate terminal energy consumption level and energy efficiency potential, analyzing the level of terminal energy consumption of public buildings in China.
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Yu, Wenhong, Shengshi Tang et Kuan Wang. « Research on Energy-saving Performance of Low-energy Consumption Green Buildings ». E3S Web of Conferences 233 (2021) : 01100. http://dx.doi.org/10.1051/e3sconf/202123301100.

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In view of the shortcomings of the current green building evaluation system, this paper present a new evaluating index for the energy saving performance of low-energy green buildings: CEC, and this paper evaluated and analyzed the energy-saving performance of green building by using CEC index.
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Komissarov, A. P., Y. A. Lagunova et O. A. Lukashuk. « Evaluation of Single-bucket Excavators Energy Consumption ». Procedia Engineering 150 (2016) : 1221–26. http://dx.doi.org/10.1016/j.proeng.2016.07.239.

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Kumar, Ashish, M. Q. Rafiq et Kamal Bansal. « Performance Evaluation of Energy Consumption in MANET ». International Journal of Computer Applications 42, no 2 (31 mars 2012) : 7–12. http://dx.doi.org/10.5120/5662-7692.

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Zhao, Guoyong, Chunhong Hou, Jianfang Qiao et Xiang Cheng. « Energy consumption characteristics evaluation method in turning ». Advances in Mechanical Engineering 8, no 11 (novembre 2016) : 168781401668073. http://dx.doi.org/10.1177/1687814016680737.

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Wang, Shuai. « Evaluation of China's Energy Strategy ». Advanced Materials Research 986-987 (juillet 2014) : 295–98. http://dx.doi.org/10.4028/www.scientific.net/amr.986-987.295.

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The energy problem is a matter of human survival and development of a global issue. With the deepening of the new industrialization, energy resources, climate change, environmental problems to human challenge is becoming more and more serious. In the development of China's energy consumption, energy consumption structure and the world in general there are many differences between the consumption structure, rational utilization of domestic coal resources, improve efficiency, promote the reform of energy-using way, will become China's energy industry development in the future be solved the problem. To build China's energy security system is not only the need of China's economic and social development, but also to enhance our voice and influence in the global energy affairs.
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Vassileva, Iana, Erik Dahlquist, Fredrik Wallin et Javier Campillo. « Energy consumption feedback devices’ impact evaluation on domestic energy use ». Applied Energy 106 (juin 2013) : 314–20. http://dx.doi.org/10.1016/j.apenergy.2013.01.059.

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Wu, Bin, et Qing Liu. « Research on Energy-Saving Evaluation System of Yangtze River Support Ships ». Advanced Materials Research 113-116 (juin 2010) : 969–73. http://dx.doi.org/10.4028/www.scientific.net/amr.113-116.969.

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The Yangtze River shipping industry has large energy consumption, which is China's key energy saving areas. Energy consumption of support ships occupies high proportion in the Yangtze River shipping industry. According to actual operating condition of the Yangtze River shipping support system, and the situation of energy-saving management, proposed the energy-saving targets for evaluation, and determined targets weight with theories of system engineering, and established the incentive mechanism of energy consumption in accord with energy conservation law and the related energy consumption standard, designs the energy saving assessment form in view of the ships navigation environment. Energy consumption levels can be seen by evaluating the targets.
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Thèses sur le sujet "Evaluation of energy consumption"

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Arokiasamy, David Balachandar. « Energy Consumption Evaluation of LoRa Technology ». Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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Lora is a wireless technology that has been developed to enable low data rate communications to be made over long distances especially for IoT applications. With growing Internet of things, Lora technology addresses the increasing demands on end devices for long range connectivity with low power battery consumption and also with low infrastructure cost to deploy. Lora utilizes a spread spectrum modulation and protocol in Sub-Ghz RF band to enable long range greater than 10 km with low power and high network capacity. In this thesis, I would like to give some comprehensive introduction about Lora specifications. As we know that Lora consumes low power to transmit the data packets given to the physical layer and the query is to know in which range of low power lies. This will be the outcome of my thesis with energy measurements for transmitting a data packet. This also includes different configurations of the devices.
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Osqui, Mitra M. 1980. « Evaluation of software energy consumption on microprocessors ». Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8344.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2002.
Includes bibliographical references (leaves 72-75).
In the area of wireless communications, energy consumption is the key design consideration. Significant effort has been placed in optimizing hardware for energy efficiency, while relatively less emphasis has been placed on software energy reduction. For overall energy efficiency reduction of system energy consumption in both hardware and software must be addressed. One goal of this research is to evaluate the factors that affect software energy efficiency and identify techniques that can be employed to produce energy optimal software. In order to present a strong argument, two state-of-the-art low power processors were used for evaluation: the Intel StrongARM SA-1100 and the next generation Intel Xscale processor. A key step in analyzing the performance of software is to perform a comprehensive tabulation of the energy consumption per instruction, while taking into account the different modes of operation. This leads into a comprehensive energy profiling for the instruction set of the processors of interest. With information on the energy consumption per instruction, we can evaluate the feasibility of energy efficient programming and use the results to gain greater insight into the power consumption of the two processors under consideration. Benchmark programs will be tested on both processors to illustrate the effectiveness of the energy profiling results. The next goal is to look at the leakage current and current consumed during idle modes of the processors and how that impacts the overall picture of energy consumption. Thus energy consumption will be explored for the two processors from both a dynamic and static energy consumption perspective.
by Mitra M. Osqui.
S.M.
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Damron, Lauren Leigh Brannom. « An energy consumption evaluation for existing, commercial buildings ». Kansas State University, 2017. http://hdl.handle.net/2097/38228.

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Master of Science
Department of Architectural Engineering and Construction Science
Julia A. Keen
The intent of this report is to recommend a process for legislation that can be used to identify commercial buildings that have the greatest potential to reduce energy consumption. A point-based evaluation is completed of current energy processes for existing commercial buildings. The recommended energy evaluation system is applied to an existing building, which allows for a detailed review of how the evaluation is completed for a building. The results are presented to display the value of assessing building energy performance. Additionally, the results reinforce the potential to transform the industry and energy use by buildings.
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Armstrong, Stephen George. « Thermal evaluation of building detail ». Thesis, University of Newcastle Upon Tyne, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387382.

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Vuppuluri, Prem Kiran. « Impact of Sustainable Cool Roof Technology on Building Energy Consumption ». PDXScholar, 2014. http://pdxscholar.library.pdx.edu/open_access_etds/1530.

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Highly reflective roofing systems have been analyzed over several decades to evaluate their ability to meet sustainability goals, including reducing building energy consumption and mitigating the urban heat island. Studies have isolated and evaluated the effects of climate, surface reflectivity, and roof insulation on energy savings, thermal load mitigation and also ameliorating the urban heat island. Other sustainable roofing systems, like green-roofs and solar panels have been similarly evaluated. The motivation for the present study is twofold: the first goal is to present a method for simultaneous evaluation and inter-comparison of multiple roofing systems, and the second goal is to quantitatively evaluate the realized heating and cooling energy savings associated with a white roof system compared to the reduction in roof-top heat flux. To address the first research goal a field experiment was conducted at the International Harvester Building located in Portland, OR. Thermal data was collected for a white roof, vegetated roof, and a solar panel shaded vegetated roof, and the heat flux through these roofing systems was compared against a control patch of conventional dark roof membrane. The second research goal was accomplished using a building energy simulation program to determine the impact of roof area and roof insulation on the savings from a white roof, in both Portland and Phoenix. The ratio of cooling energy savings to roof heat flux reduction from replacing a dark roof with a white roof was 1:4 for the month of July, and 1:5 annually in Portland. The COP of the associated chillers ranges from 2.8-4.2, indicating that the ratio of cooling energy savings to heat flux reduction is not accounted for solely by the COP of the chillers. The results of the building simulation indicate that based on energy savings alone, white roofs are not an optimal choice for Portland. The benefits associated with cooling energy savings relative to a black roof are offset by the winter-time penalty, and the net benefit from adopting white roof technology in Portland is small. That said, there are other potential benefits of white roofing such as impact on urban heat islands and roof life that must also be considered.
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Sanaboyina, Tulasi Priyanka. « Performance Evaluation of Time series Databases based on Energy Consumption ». Thesis, Blekinge Tekniska Högskola, Institutionen för kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13593.

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The vision of the future Internet of Things is posing new challenges due to gigabytes of data being generated everyday by millions of sensors, actuators, RFID tags, and other devices. As the volume of data is growing dramatically, so is the demand for performance enhancement. When it comes to this big data problem, much attention has been given to cloud computing and virtualization for their almost unlimited resource capacity, flexible resource allocation and management, and distributed processing ability that promise high scalability and availability. On the other hand, the variety of types and nature of data is continuously increasing. Almost without exception, data centers supporting cloud based services are monitored for performance and security and the resulting monitoring data needs to be stored somewhere. Similarly, billions of sensors that are scattered throughout the world are pumping out huge amount of data, which is handled by a database. Typically, the monitoring data consists time series, that is numbers indexed by time. To handle this type of time series data a distributed time series database is needed.   Nowadays, many database systems are available but it is difficult to use them for storing and managing large volumes of time series data. Monitoring large amounts of periodic data would be better done using a database optimized for storing time series data. The traditional and dominant relational database systems have been questioned whether they can still be the best choice for current systems with all the new requirements. Choosing an appropriate database for storing huge amounts of time series data is not trivial as one must take into account different aspects such as manageability, scalability and extensibility. During the last years NoSQL databases have been developed to address the needs of tremendous performance, reliability and horizontal scalability. NoSQL time series databases (TSDBs) have risen to combine valuable NoSQL properties with characteristics of time series data from a variety of use-cases.   In the same way that performance has been central to systems evaluation, energy-efficiency is quickly growing in importance for minimizing IT costs. In this thesis, we compared the performance of two NoSQL distributed time series databases, OpenTSDB and InfluxDB, based on the energy consumed by them in different scenarios, using the same set of machines and the same data. We evaluated the amount of energy consumed by each database on single host and multiple hosts, as the databases compared are distributed time series databases. Individual analysis and comparative analysis is done between the databases. In this report we present the results of this study and the performance of these databases based on energy consumption.
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Sakva, Denys. « Evaluation of errors in national energy forecasts / ». Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/1166.

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Vahdati, Maria Malahat. « Evaluation of a two fluid ejector-compressor applicable to a domestic heat pump ». Thesis, University of Bristol, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295657.

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Hashim, Nizar Hessain. « Evaluation of alternative thermal strategies for the precast concrete system houses in Jeddah, Saudi Arabia ». Thesis, Cardiff University, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358781.

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Westin, Jonathan. « Evaluation of energy consumption in virtualization environments : Proof of concept using containers ». Thesis, Umeå universitet, Institutionen för datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-142550.

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The demand for cloud services offering virtualization increases with a continual interest for different types of applications. Regardless of the resource demand of the application, some supplier is billing by the time of usage, making it an unfair pricing for the clients. In this thesis, the virtualization characterization and properties make room for another form of payment qualities. Since power consumption is comprehensible and an understandable measurement for both parties it is investigated if there are any useful ways of measuring energy consumption of an application. The thesis creates a proof of concept of predicting energy consumption from CPU usage from a containerized application. With an empirical simulation and the use of linear regression, the results are feasible of estimating the energy consumption from the simulation data with a 0.813 Watt deviation. Even though the proof of concept is a harsh simplification of the dilemma for predicting energy consumption from an application, the thesis embraces the issue of energy consumption within data centers.
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Livres sur le sujet "Evaluation of energy consumption"

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Council, World Energy. Energy efficiency : A worldwide review : indicators, policies, evaluation. London : World Energy Council, 2004.

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Uganda. Ministry of Finance, Planning, and Economic Development. Energy for rural transformation monitoring and evaluation component. Kampala : Ministry of Finance, Planning, and Economic Development, 2008.

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Zajac, Pawel. Evaluation Method of Energy Consumption in Logistic Warehouse Systems. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22044-4.

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Douglass, John G. Evaluation of field data acquisition system : RCDP data logger project. [Olympia, Wash : Washington State Energy Office, 1988.

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Nadel, Steven. Market transformation evaluation : A tale of four regions. Washington, D.C : American Council for an Energy-Efficient Economy, 1999.

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New York State Energy Research and Development Authority. Municipal wastewater treatment plant energy evaluation : Summary report. Albany, N.Y : NYSERDA, 2006.

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Vermont. Office of the State Auditor. Turning up the heat on savings : Special report : issues, observations, & recommendations to improve the oversight and management of the state agency energy plan. [Montpelier, Vt.] : Office of the State Auditor, 2004.

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Nadel, Steven. Leading the way : Continued opportunities for new state appliance and equipment efficiency standards. Washington, DC : American Council for an Energy-Efficient Economy, 2006.

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Lee, A. D. Impact evaluation for the manufactured housing acquisition program (MAP). Richland, Wash : Pacific Northwest Laboratory, 1995.

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Skumatz, Lisa A. Bonneville measure life study : Effect of commercial building changes on energy using equipment, final report. Seattle, WA : Synergic Resources Corporation, 1991.

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Chapitres de livres sur le sujet "Evaluation of energy consumption"

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Hohmeyer, Olav. « Social Costs of Energy Consumption : Evaluation and Policy Implications ». Dans Social Costs of Energy Consumption, 15–21. Berlin, Heidelberg : Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83499-8_3.

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Franzese, Pier Paolo, Giovanni Fulvio Russo et Sergio Ulgiati. « Geographical Information System (GIS) and Emergy Synthesis Evaluation of Urban waste Management ». Dans Sustainable Energy Production and Consumption, 339–52. Dordrecht : Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-8494-2_23.

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Allard, Géraud, Pascale Minet, Dang-Quan Nguyen et Nirisha Shrestha. « Evaluation of the Energy Consumption in MANET ». Dans Ad-Hoc, Mobile, and Wireless Networks, 170–83. Berlin, Heidelberg : Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11814764_15.

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Mu, Ruiqi, Feng Gao, Hongwei Zhao, Fei Xia et Yufei Fu. « Simulation of EMU : Vehicle Energy Consumption Evaluation ». Dans Proceedings of the 5th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 2021, 82–89. Singapore : Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9913-9_10.

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Ait El Mahjoub, Youssef, Jean-Michel Fourneau et Hind Castel-Taleb. « Performance Evaluation and Energy Consumption for DVFS Processor ». Dans Lecture Notes in Computer Science, 165–80. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91825-5_10.

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Papadopoulos, Sokratis, et Elie Azar. « Multi-objective Genetic Algorithm Optimization of HVAC Operation : Integrating Energy Consumption, Thermal Comfort, and Productivity ». Dans Energy Systems Evaluation (Volume 2), 261–78. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67376-5_11.

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Nakajima, Shin, et Si-Mohamed Lamraoui. « Fault Localization of Energy Consumption Behavior Using Maximum Satisfiability ». Dans Cyber Physical Systems. Design, Modeling, and Evaluation, 99–115. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25141-7_8.

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Zajac, Pawel. « Methods to Assess the Energy Consumption of LSM ». Dans Evaluation Method of Energy Consumption in Logistic Warehouse Systems, 31–91. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22044-4_4.

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Li, Gongfa, Jianyi Kong, Guozhang Jiang, Hua Zhang, Zhigang Jiang, Gang Zhao et Liangxi Xie. « Energy Efficiency Evaluation for Iron and Steel High Energy Consumption Enterprise ». Dans Communications in Computer and Information Science, 684–90. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19853-3_101.

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Zajac, Pawel. « Verification of the Model Evaluation of LSM ». Dans Evaluation Method of Energy Consumption in Logistic Warehouse Systems, 95–123. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22044-4_6.

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Actes de conférences sur le sujet "Evaluation of energy consumption"

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Gomes, Carlos, Eduardo Tavares et Meuse Nogueira De O. Junior. « Energy Consumption Evaluation of NoSQL DBMSs ». Dans XV Workshop em Desempenho de Sistemas Computacionais e de Comunicação. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/wperformance.2016.9729.

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Over the years, NoSQL Database Management Systems (DBMS) have been adopted as an alternative to the constraints of relational/SQL DBMSs. In order to demonstrate their feasibility, works have evaluated NoSQL DBMSs regarding some performance metrics, but energy consumption has not been assessed. Indeed, energy consumption is an issue that should not be neglected due to the rise of energy costs and environmental sustainability. This paper presents a peformance and energy consumption evaluation of NoSQL DBMSs, more specifically, Cassandra (column), MongoDB (document-oriented), Redis (key-value). Experiments are based on YCSB benchmark, and results demonstrate energy consumption can vary significantly among the assessed DBMSs for different commands (e.g., read) and workloads.
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Pentikousis, Kostas. « Pitfalls in energy consumption evaluation studies ». Dans 2009 6th International Symposium on Wireless Communication Systems (ISWCS 2009). IEEE, 2009. http://dx.doi.org/10.1109/iswcs.2009.5285331.

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Xiaotong Du, Wenjian Cai et Lei Jia. « Air-conditioning system energy efficiency and energy consumption evaluation ». Dans 2010 8th World Congress on Intelligent Control and Automation (WCICA 2010). IEEE, 2010. http://dx.doi.org/10.1109/wcica.2010.5554546.

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Delgado-Gomes, Vasco, Jose A. Oliveira-Lima, Celson Lima, Joao F. Martins, Ricardo Jardim-Goncalves et Vitor Fernao Pires. « Energy consumption evaluation to reduce manufacturing costs ». Dans 2013 IV International Conference on Power Engineering, Energy and Electrical Drives (POWERENG). IEEE, 2013. http://dx.doi.org/10.1109/powereng.2013.6635749.

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Ghariani, Takoua, et Badii Jouaber. « Energy consumption evaluation for LTE scheduling algorithms ». Dans 2015 International Symposium on Networks, Computers and Communications (ISNCC). IEEE, 2015. http://dx.doi.org/10.1109/isncc.2015.7238594.

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Noh, Hae Young, et Ram Rajagopal. « Data-driven forecasting algorithms for building energy consumption ». Dans SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, sous la direction de Jerome P. Lynch, Chung-Bang Yun et Kon-Well Wang. SPIE, 2013. http://dx.doi.org/10.1117/12.2009894.

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Astakhov, Viktor P., et Xinran Xiao. « Cutting Force Evaluation Based On Total Energy Consumption ». Dans SAE World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2008. http://dx.doi.org/10.4271/2008-01-1131.

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Kandari, Sonika, et M. K. Pandey. « Evaluation of energy consumption by nodes of MANET ». Dans 2015 National Conference on Recent Advances in Electronics & Computer Engineering (RAECE). IEEE, 2015. http://dx.doi.org/10.1109/raece.2015.7510221.

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Princhak, Gabriel, et Karen Pontes. « EVALUATION OF ENERGY CONSUMPTION IN A METHANOL PLANT ». Dans 18th Brazilian Congress of Thermal Sciences and Engineering. ABCM, 2020. http://dx.doi.org/10.26678/abcm.encit2020.cit20-0474.

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Song, Shutong, Fadi Wedyan et Yaser Jararweh. « Empirical Evaluation of Energy Consumption for Mobile Applications ». Dans 2021 12th International Conference on Information and Communication Systems (ICICS). IEEE, 2021. http://dx.doi.org/10.1109/icics52457.2021.9464579.

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Rapports d'organisations sur le sujet "Evaluation of energy consumption"

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Tawil, J. J. Statistical evaluation of Pacific Northwest Residential Energy Consumption Survey weather data. Office of Scientific and Technical Information (OSTI), février 1986. http://dx.doi.org/10.2172/6216833.

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Yashar, David A., et Young-Jin Baik. Evaluation of Energy Consumption Rating Methods for Thermoelectric Wine Chillers and Compact Refrigerators. National Institute of Standards and Technology, septembre 2013. http://dx.doi.org/10.6028/nist.ir.7963.

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Archer, Christopher. Planning Strategies for Transportation Fuel Consumption Reduction : An Evaluation of the Hawaii Clean Energy Initiative's Transportation Plan. Fort Belvoir, VA : Defense Technical Information Center, avril 2014. http://dx.doi.org/10.21236/ada610484.

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Kurnik, Charles W., Ken Agnew et Mimi Goldberg. Chapter 8 : Whole-Building Retrofit with Consumption Data Analysis Evaluation Protocol. The Uniform Methods Project : Methods for Determining Energy Efficiency Savings for Specific Measures. Office of Scientific and Technical Information (OSTI), novembre 2017. http://dx.doi.org/10.2172/1407847.

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Author, Not Given. Household vehicles energy consumption, 1988. Office of Scientific and Technical Information (OSTI), février 1990. http://dx.doi.org/10.2172/7154211.

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Flanagan, D. M., H. J. Tsao, R. L. Jr Schmoyer et J. M. MacDonald. Nonresidential Building Energy Consumption Survey (NBECS). Office of Scientific and Technical Information (OSTI), octobre 1990. http://dx.doi.org/10.2172/6393534.

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Author, Not Given. Household energy consumption and expenditures 1987. Office of Scientific and Technical Information (OSTI), janvier 1990. http://dx.doi.org/10.2172/5127577.

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Yourtchenko, A., et L. Colitti. Reducing Energy Consumption of Router Advertisements. RFC Editor, février 2016. http://dx.doi.org/10.17487/rfc7772.

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Jerald Brevick, clark Mount-Campbell et Carroll Mobley. Energy Consumption of Die Casting Operations. Office of Scientific and Technical Information (OSTI), mars 2004. http://dx.doi.org/10.2172/822409.

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Szydlowski, R. F., et W. D. Jr Chvala. Energy consumption of personal computer workstations. Office of Scientific and Technical Information (OSTI), février 1994. http://dx.doi.org/10.2172/10134947.

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