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Статті в журналах з теми "Energy conservation – Ontario – Forecasting"
Rodriguez, C. P., and G. J. Anders. "Energy Price Forecasting in the Ontario Competitive Power System Market." IEEE Transactions on Power Systems 19, no. 1 (February 2004): 366–74. http://dx.doi.org/10.1109/tpwrs.2003.821470.
Повний текст джерелаFarmer, David J., and Layne N. Thiessen. "Recent Regulatory and Legislative Developments of Interest to Energy Lawyers." Alberta Law Review 51, no. 2 (December 1, 2013): 427. http://dx.doi.org/10.29173/alr73.
Повний текст джерелаLópez, Karol Lina, Christian Gagné, Germán Castellanos-Dominguez, and Mauricio Orozco-Alzate. "Training subset selection in Hourly Ontario Energy Price forecasting using time series clustering-based stratification." Neurocomputing 156 (May 2015): 268–79. http://dx.doi.org/10.1016/j.neucom.2014.12.052.
Повний текст джерелаXie, Hui, Li Feng Wang, and Wei Liang. "Forecasting of Energy Consumption of Beijing's Residential Sector Based on System Dynamics Model." Advanced Materials Research 869-870 (December 2013): 537–40. http://dx.doi.org/10.4028/www.scientific.net/amr.869-870.537.
Повний текст джерелаGao, Lei. "Forecasting and Analysis of Energy Consumption in China." Frontiers in Business, Economics and Management 3, no. 2 (March 16, 2022): 26–30. http://dx.doi.org/10.54097/fbem.v3i2.257.
Повний текст джерелаDeng, Zhuofu, Xianglong Qi, Tengteng Xu, and Yingnan Zheng. "Operational Scheduling of Behind-the-Meter Storage Systems Based on Multiple Nonstationary Decomposition and Deep Convolutional Neural Network for Price Forecasting." Computational Intelligence and Neuroscience 2022 (February 21, 2022): 1–18. http://dx.doi.org/10.1155/2022/9326856.
Повний текст джерелаRunge, Jason, and Radu Zmeureanu. "Forecasting Energy Use in Buildings Using Artificial Neural Networks: A Review." Energies 12, no. 17 (August 23, 2019): 3254. http://dx.doi.org/10.3390/en12173254.
Повний текст джерелаLarroque, Jeremy, Julian Wittische, and Patrick M. A. James. "Quantifying and predicting population connectivity of an outbreaking forest insect pest." Landscape Ecology 37, no. 3 (December 23, 2021): 763–78. http://dx.doi.org/10.1007/s10980-021-01382-9.
Повний текст джерелаSmith, L. E., Marie H. Buchinski, and And Deirdre A. Sheehan. "Recent Regulatory and Legislative Developments of Interest to Energy Lawyers." Alberta Law Review 48, no. 2 (December 1, 2010): 417. http://dx.doi.org/10.29173/alr160.
Повний текст джерелаWei, Shangfu, and Xiaoqing Bai. "Multi-Step Short-Term Building Energy Consumption Forecasting Based on Singular Spectrum Analysis and Hybrid Neural Network." Energies 15, no. 5 (February 25, 2022): 1743. http://dx.doi.org/10.3390/en15051743.
Повний текст джерелаДисертації з теми "Energy conservation – Ontario – Forecasting"
Dodds, Gordon Ivan. "Modelling and forecasting electricity demand using aggregate and disaggregate data." Thesis, Queen's University Belfast, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306073.
Повний текст джерелаMcCafferty, Peter. "Forecasting electricity demand in the industrial sector based on disaggregate data." Thesis, Queen's University Belfast, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385049.
Повний текст джерелаHadjipaschalis, Constantinos. "An investigation of artificial neural networks applied to monthly electricity peak demand and energy forecasting." Thesis, Imperial College London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286627.
Повний текст джерелаMotsomi, Abel Pholo. "Statistical tools for consolidation of energy demand forecasts." Thesis, Nelson Mandela Metropolitan University, 2012. http://hdl.handle.net/10948/d1011578.
Повний текст джерелаMedjiah, Samir. "Optimisation des protocoles de routage dans les réseaux multi-sauts sans fil à contraintes." Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14663/document.
Повний текст джерелаGreat research efforts have been carried out in the field of challenged multihop wireless networks (MWNs). Thanks to the evolution of the Micro-Electro-Mechanical Systems (MEMS) technology and nanotechnologies, multihop wireless networks have been the solution of choice for a plethora of problems. The main advantage of these networks is their low manufacturing cost that permits one-time application lifecycle. However, if nodes are low-costly to produce, they are also less capable in terms of radio range, bandwidth, processing power, memory, energy, etc. Thus, applications need to be carefully designed and especially the routing task because radio communication is the most energy-consuming functionality and energy is the main issue for challenged multihop wireless networks.The aim of this thesis is to analyse the different challenges that govern the design of challenged multihop wireless networks such as applications challenges in terms of quality of service (QoS), fault-tolerance, data delivery model, etc., but also networking challenges in terms of dynamic network topology, topology voids, etc. Our contributions in this thesis focus on the optimization of routing under different application requirements and network constraints. First, we propose an online multipath routing protocol for QoS-based applications using wireless multimedia sensor networks. The proposed protocol relies on the construction of multiple paths while transmitting data packets to their destination, i.e. without prior topology discovery and path establishment. This protocol achieves parallel transmissions and enhances the end-to-end transmission by maximizing path bandwidth and minimizing the delays, and thus meets the requirements of QoS-based applications. Second, we tackle the problem of routing in mobile delay-tolerant networks by studying the intermittent connectivity of nodes and deriving a contact model in order to forecast future nodes' contacts. Based upon this contact model, we propose a routing protocol that makes use of nodes' locations, nodes' trajectories, and inter-node contact prediction in order to perform forwarding decisions. The proposed routing protocol achieves low end-to-end delays while using efficiently constrained nodes' resources in terms of memory (packet queue occupancy) and processing power (forecasting algorithm). Finally, we present a topology control mechanism along a packet forwarding algorithm for event-driven applications using stationary wireless sensor networks. Topology control is achieved by using a distributed duty-cycle scheduling algorithm. Algorithm parameters can be tuned according to the desired node's awake neighbourhood size. The proposed topology control mechanism ensures trade-off between event-reporting delay and energy consumption
MacPherson, Jerry R. "Long-term energy demand forecasting : determination of an energy baseline and energy conservation supply curves for the Manitoba Health Care subsector." 1989. http://hdl.handle.net/1993/22867.
Повний текст джерелаSchembri, Jeremy. "The Influence of Home Energy Management Systems on the Behaviours of Residential Electricity Consumers: An Ontario, Canada Case Study." Thesis, 2008. http://hdl.handle.net/10012/4029.
Повний текст джерелаDeline, Mary Elizabeth. "Keeping Up With the Joneses: Electricity Consumption, Publicity and Social Network Influence in Milton, Ontario." Thesis, 2010. http://hdl.handle.net/10012/5219.
Повний текст джерелаSimmons, Sarah Ivy. "Investigating the impacts of time-of-use electricity rates on lower-income and senior-headed households: A case study of Milton, Ontario (Canada)." Thesis, 2010. http://hdl.handle.net/10012/5041.
Повний текст джерелаКниги з теми "Energy conservation – Ontario – Forecasting"
Canada. Library of Parliament. Science and Technology Division. and Canada. Library of Parliament. Research Branch., eds. Energy efficiency: Future improvement. Ottawa: Research Branch, Library of Parliament, 1992.
Знайти повний текст джерелаAn energy efficient Ontario: Toward the year 2000. [Toronto]: The Ministry, 1986.
Знайти повний текст джерелаOrganization for Economic Co-operation and Development. World energy outlook. Paris: OECD, 1996.
Знайти повний текст джерелаEnergy, Ontario Ministry of. Energy 2000: An Energy Efficient Ontario. Description of Various Programs For Greater Energy Conservation. S.l: s.n, 1986.
Знайти повний текст джерелаEnergy, Ontario Ministry of. Energy trends in Ontario: A five part series. Toronto, ON: Ministry of Energy, 1986.
Знайти повний текст джерелаJenkins, Jeremy. A summary report on the design and construction of 5 retrofitted houses and a low energy new house in Armstrong, Ontario: Remote low energy housing demonstration for the Ontario Ministry of Energy. Toronto, Ont: Ontario Ministry of Energy, 1985.
Знайти повний текст джерелаMcRuer, John D. Sustainable energy?: A case study of Ontario :a report submitted to the Conservation Council of Ontario, February 1994. Toronto: Conservation Council of Ontario, 1995.
Знайти повний текст джерелаUniversity of Texas at Austin. Center for Transportation Research. Texas transportation energy savings: Strategies for reducing energy consumption. Austin, Tex: Texas Sustainabale Energy Development Council, 1995.
Знайти повний текст джерелаIvanov, Valentin Borisovich. Puti vovlechenii︠a︡ nevostrebovannykh toplivno-mineralʹnykh resursov Rossii: Sbornik prognozno-analiticheskikh ot︠s︡enok i tekhnologicheskikh predpolozheniĭ za period do 2050 g. Moskva: Novosti teplosnabzhenii︠a︡, 2011.
Знайти повний текст джерелаHydro, Ontario. Ontario Hydro's demand/supply plan. Toronto, Ont: Province of Ontario, 1990.
Знайти повний текст джерелаЧастини книг з теми "Energy conservation – Ontario – Forecasting"
Copeland, Holly E., Kevin E. Doherty, David E. Naugle, Amy Pocewicz, and Joseph M. Kiesecker. "Forecasting Energy Development Scenarios to Aid in Conservation Design." In Energy Development and Wildlife Conservation in Western North America, 183–93. Washington, DC: Island Press/Center for Resource Economics, 2011. http://dx.doi.org/10.5822/978-1-61091-022-4_10.
Повний текст джерелаKumar, Sachin, Saibal K. Pal, and Ram Pal Singh. "Intelligent Energy Conservation: Indoor Temperature Forecasting with Extreme Learning Machine." In Advances in Intelligent Systems and Computing, 977–88. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47952-1_78.
Повний текст джерелаMcDonald, J. R., K. L. Lo, and T. M. Taha. "INCORPORATION OF CONSERVATION MEASURES IN LONG TERM ELECTRICITY DEMAND FORECASTING." In Energy and the Environment, 465–71. Elsevier, 1990. http://dx.doi.org/10.1016/b978-0-08-037539-7.50079-x.
Повний текст джерелаТези доповідей конференцій з теми "Energy conservation – Ontario – Forecasting"
Norrie, Steven J., and Peter Love. "Creating a culture of conservation in ontario: Approaches, challenges and opportunities." In Energy Society General Meeting (PES). IEEE, 2009. http://dx.doi.org/10.1109/pes.2009.5275904.
Повний текст джерелаZareipour, H., K. Bhattacharya, and C. A. Canizares. "Forecasting the hourly Ontario energy price by multivariate adaptive regression splines." In 2006 IEEE Power Engineering Society General Meeting. IEEE, 2006. http://dx.doi.org/10.1109/pes.2006.1709474.
Повний текст джерелаAnders, George J., and Claudia Rodriguez. "Energy price forecasting and bidding strategy in the Ontario power system market." In 2005 IEEE Russia Power Tech. IEEE, 2005. http://dx.doi.org/10.1109/ptc.2005.4524367.
Повний текст джерелаMandal, P., A. U. Haque, Julian Meng, R. Martinez, and A. K. Srivastava. "A hybrid intelligent algorithm for short-term energy price forecasting in the Ontario market." In 2012 IEEE Power & Energy Society General Meeting. New Energy Horizons - Opportunities and Challenges. IEEE, 2012. http://dx.doi.org/10.1109/pesgm.2012.6345461.
Повний текст джерелаPany, Prasanta Kumar, and S. P. Ghoshal. "Forecasting the hourly Ontario energy price by local linear wavelet neural network and ARMA models." In the International Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2007052.2007091.
Повний текст джерелаTao Hong and Pu Wang. "On the impact of demand response: Load shedding, energy conservation, and further implications to load forecasting." In 2012 IEEE Power & Energy Society General Meeting. New Energy Horizons - Opportunities and Challenges. IEEE, 2012. http://dx.doi.org/10.1109/pesgm.2012.6345192.
Повний текст джерелаAhmadi, Lena, Woramon Unbangluang, Eric Croiset, Ali Elkamel, Peter L. Douglas, Evgueniy Entchev, and Hong-Ming Ku. "Forecasting the Impact of Plug-In Hybrid Electric Vehicles Penetration on Ontario’s Electricity Grid." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-38240.
Повний текст джерелаDoiphode, Ganesh, and Hamidreza Najafi. "A Machine Learning Based Approach for Energy Consumption Forecasting in K-12 Schools." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-24128.
Повний текст джерелаGori, Fabio. "Preliminary Results for Forecasting the Oil Price Evolution With Negative Inflation Rate." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-86729.
Повний текст джерелаConry, Patrick, H. J. S. Fernando, L. S. Leo, Ashish Sharma, Mark Potosnak, and Jessica Hellmann. "Multi-Scale Simulations of Climate-Change Influence on Chicago Heat Island." In ASME 2014 4th Joint US-European Fluids Engineering Division Summer Meeting collocated with the ASME 2014 12th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/fedsm2014-21581.
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