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Prediction of reservoir permeability from porosity measurements for the upper sandstone member of Zubair Formation in Super-Giant South Rumila oil field, southern Iraq, using M5P decision tress and adaptive neuro-fuzzy inference system (ANFIS): a comparative study
2016
Modeling Earth Systems and Environment
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This study focus on the determining the reservoir permeability from measured porosity using different techniques namely linear regression, adaptive neuro-fuzzy inference system, and M5 decision trees. ...
The models performances were evaluated using root mean squared error (RMSE) and coefficient of determination (R 2 ) error statistics. ...
Modeling techniques ANFIS ANFIS is a hybrid soft computing technique which has the potential to capture the benefits of artificial neural network technique (ANN) and fuzzy inference system (FIS). ...
doi:10.1007/s40808-016-0179-6
fatcat:5sadljccqzgf7gomkskx3a7okq
SOCRATES: A system for scheduling hydroelectric generation under uncertainty
1995
Annals of Operations Research
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SOCRATES is a system for the optimal scheduling of PG&E's various energy sources over a one-to two-year horizon. This paper concentrates on the component of SOCRATES that schedules hydro. ...
The core is a stochastic optimization model, solved using Benders decomposition. Additional components are streamflow forecasting models and a database containing hydrological information. ...
Earlier work at PG&E by Eleanor Feingold and Jerson Kelman on similar topics also helped us to get started in the right direction. We credit Ali Vojdani for instigating this R&D project. ...
doi:10.1007/bf02031745
fatcat:xhzk3roqerf5nfo2e37jior4ri
Approaches to optimal aquifer management and intelligent control in a multiresolutional decision support system
2005
Hydrogeology Journal
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Despite remarkable new developments in stochastic hydrology and adaptations of advanced methods from operations research, stochastic control, and artificial intelligence, solutions of complex real-world ...
A paradigm shift is introduced: an adaptation of new methods of intelligent control that will relax the dependency on rigid, computer-intensive, stochastic PDE, and will shift the emphasis to a goal-oriented ...
Dong Zhang (U. of Oklahoma), Dr. S.P. Neumann (U. of Arozina), and Dr. Larry Lake (U. of Texas). ...
doi:10.1007/s10040-004-0424-3
fatcat:h4bzzrojfjehncrpxnihapyjka
Towards Observability for Production Machine Learning Pipelines
[article]
2022
arXiv
pre-print
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Many of these tools facilitate the initial development of ML applications, but sustaining these applications post-deployment is difficult due to lack of real-time feedback (i.e., labels) for predictions ...
Finally, we introduce an example architecture for a "bolt-on" ML observability system, or one that wraps around existing tools in the stack. ...
To minimize log size, we can use the same approach as in the previous section and use a reservoir sample for prediction tuples; a uniform sample may suffice for training tuples. ...
arXiv:2108.13557v3
fatcat:2spgtlelnzg4tmmcgey4qhdplq
Multiple Model Predictive Flood Control in Regulated River Systems with Uncertain Inflows
2012
Water resources management
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The performance of the approach is demonstrated using a simulated river-reservoir model as well as using data collected at the Wivenhoe Dam during the 2011 floods in Queensland, Australia. ...
Optimal model selection is achieved in a minimum mean square error sense using a bank of Kalman filters to identify the most likely inflow characteristic. ...
The benefits of MPC are, its ability to incorporate external disturbances to the system model and the convenience of applying constraints. ...
doi:10.1007/s11269-012-0214-y
fatcat:oaclnurkznefbkzfeoxizgok7e
High-Performance Integrated Control of water quality and quantity in urban water reservoirs
2015
Water Resources Research
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The framework is used to design the hourly operation of Marina Reservoir, a 3.2 Mm 3 storm-water-fed reservoir located in the center of Singapore, operated for drinking water supply and flood control. ...
describe Key Points: A novel computational framework to real-time operation of urban reservoirs The approach combines model reduction and model predictive control Water quality and drinking supply are ...
Acknowledgments The data used in this study were provided by Singapore's Public Utilities Board in the context of the Singapore-Delft Water Alliance Multi-Objective Multiple-Reservoir Management research ...
doi:10.1002/2015wr017595
fatcat:pl7nveczjzbihcnop6ciqxngvq
A microfluidic passive pumping Coulter counter
2010
Microfluidics and Nanofluidics
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Flow occurred due to a Young-Laplace pressure gradient between two 1.2 mm diameter inlets and a 4 mm diameter reservoir when 0.5μ L fluid droplets were applied to the inlets using a micropipette. ...
Polystyrene particles (10μm diameter) were enumerated using the resistive pulse technique. Particle counts using passive pumping were within 13% of counts from a device using syringe pumping. ...
For increased portability, the entire experimental device could ultimately be condensed into a hand-held point-of-use tool by replacing the desktop computer with a battery-powered micro-controller programmed ...
doi:10.1007/s10404-010-0609-0
pmid:23930109
pmcid:PMC3735229
fatcat:nkwblxnjb5d2pbtxvvtnohwqby
Projection of Future Hydropower Generation in Samanalawewa Power Plant, Sri Lanka
2020
Mathematical Problems in Engineering
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The projected results are of utmost importance to stakeholders to manage reservoir operations while maximizing the productivity of the impounded water and thus, maximizing economic growth as well as social ...
benefits. ...
supports ANN models to be one of the powerful soft computing tools in predicting future hydropower generation either from minihydropower type or reservoir type hydropower plant, still deep understanding ...
doi:10.1155/2020/8862067
fatcat:dbw6hrxnbbcgbe3apkqryjoxei
IOT Automation with Segmentation Techniques for Detection of Plant Seedlings in Agriculture
2022
Wireless Communications and Mobile Computing
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conditions of the external environment without the use of light control or more specific hardware. ...
The present work proposes to evaluate, compare, and determine software alternatives that present good detection performance and low computational cost for the plant segmentation operation in computer vision ...
increase) for the personal computer, thus increasing the computational cost of the system operation to 80%. ...
doi:10.1155/2022/6466555
fatcat:icxs4ku2tnha3enrj7uo57jwtq
Advanced 3D printed model of middle cerebral artery aneurysms for neurosurgery simulation
2019
3D Printing in Medicine
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Computer-aided design (CAD) models and pre-existing computational 3D models were also incorporated in the development of the simulator. ...
Neurosurgical residents are finding it more difficult to obtain experience as the primary operator in aneurysm surgery. ...
The benefits of casting materials with a reduced shore hardness improved soft tissue representation. ...
doi:10.1186/s41205-019-0048-9
pmid:31372773
pmcid:PMC6743137
fatcat:szycvhaa4ncxlb24j4gbo3opwu
Development of soft computing and applications in agricultural and biological engineering
2010
Computers and Electronics in Agriculture
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This paper reviews the development of soft computing techniques. ...
Soft computing is a set of "inexact" computing techniques, which are able to model and analyze very complex problems. ...
Methods of soft computing In general, soft computing includes the methods of FL, neuro-computing, evolutionary computing, probabilistic computing, belief networks, chaotic systems, and parts of learning ...
doi:10.1016/j.compag.2010.01.001
fatcat:quszrg4vuzgcvkh2uglutnujdm
Memristors – from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing
[article]
2020
arXiv
pre-print
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To argue that lessons from biology can be useful in providing directions for further progress in artificial intelligence, we briefly discuss an example based reservoir computing. ...
We conclude the review by speculating on the big picture view of future neuromorphic and brain-inspired computing systems. ...
We claim that reservoir computing would benefit from appropriate hardware. ...
arXiv:2004.14942v1
fatcat:b52hrjk365f2tabarxg4zfys44
Data assimilation in hydrodynamic models for system-wide soft sensing and sensor validation for urban drainage tunnels
2020
Journal of Hydroinformatics
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Tunnels are increasingly used worldwide to expand the capacity of urban drainage systems, but they are difficult to monitor with sensors alone. ...
This study enables soft sensing of urban drainage tunnels by assimilating water level observations into an ensemble of hydrodynamic models. ...
This work is part of a joint PhD programme between the Technical University of Denmark and the Nanyang Technological University, Singapore. ...
doi:10.2166/hydro.2020.074
fatcat:xvt65dit7rbktewzyxnbfhuasi
Impact of the quality of hydrological forecasts on the management and revenue of hydroelectric reservoirs – a conceptual approach
2021
Hydrology and Earth System Sciences
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The operation of hydropower systems, including the management of water stored in reservoirs, is thus partially impacted by weather and hydrological conditions. ...
The improvement of a forecasting system and the continuous evaluation of its quality are recurrent steps in operational practice. ...
Multiple uses of water can also benefit from betterinformed hydropower operations. ...
doi:10.5194/hess-25-1033-2021
fatcat:5zv7pc4jvfdmloguzcj6qqqg7i
Integrated Operation of Multi-Reservoir and Many-Objective System Using Fuzzified Hedging Rule and Strength Pareto Evolutionary Optimization Algorithm (SPEA2)
2021
Water
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In this paper, a many-objective optimization algorithm was developed using SPEA2 for a system of four reservoirs in the Karun basin, including hydropower, municipal and industrial, agricultural, and environmental ...
SPEA2 was used to optimize hedging coefficients using the first 43 years of data and the last 10 years of data were used to test the optimized rule curves. ...
Minimizing Variance of Reservoir Systems Operations Benefits using Soft Computing
Tools. Fuzzy Sets Syst. 2003, 139, 451–461. [CrossRef]
13. Dubrovin, T.; Jolma, A.; Turunen, E. ...
doi:10.3390/w13151995
fatcat:7uf6b4s3oje63o7aaf4ltp4ls4
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