systemmodeling and optimization Xx [electronic Resource] : Ifip Tc7 20th conference on system modeling and optimization July 23-27, 2001, Trier, Germany by Sachs, E. W; Tichatschke, R; published by Boston, Ma : Sprin...
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systemmodeling and optimization Xx [electronic Resource] : Ifip Tc7 20th conference on system modeling and optimization July 23-27, 2001, Trier, Germany by Sachs, E. W; Tichatschke, R; published by Boston, Ma : Springer US
the proceedings contain 14 papers. the topics discussed include: use of convolutional neural networks for identifying additional features on a digital image of human face;diversification of stock portfolio structure u...
the proceedings contain 14 papers. the topics discussed include: use of convolutional neural networks for identifying additional features on a digital image of human face;diversification of stock portfolio structure under market restrictions;a mobile facial recognition system based on a set of raspberry technical tools;the regularized operator extrapolation algorithm for variational inequalities;text classification using term co-occurrence matrixod;medical card information system for data analysis from fitness bracelets;quantile-based statistical techniques for anomaly detection;machine learning for remote monitoring of agricultural fields with explosive tunnels;example of chaotic behavior in systems of ordinary differential equations arising in modeling of gene regulatory networks;and a nonlinear autonomous boundary value problem for a non-degenerate differential-algebraic system.
the proceedings contain 15 papers. the topics discussed include: optimizing network economics problem with adaptive algorithms for variational inequalities;simulated datasets generator for testing data analytics metho...
the proceedings contain 15 papers. the topics discussed include: optimizing network economics problem with adaptive algorithms for variational inequalities;simulated datasets generator for testing data analytics methods;simulated datasets generator for testing data analytics methods;dynamic rebalancing of cryptocurrency portfolio based on forecasted technical indicators and random forest method;automation and management in operating systems: the role of artificial intelligence and machine learning;regularity of geotechnological formation of the area of weakened connections in the rock mass;simulation the impact of time-delay in Richardson arms race models;Adomian decomposition method in the theory of nonlinear periodic boundary value problems with delay;approximation of systems with delay and their application;and control actions using voice and gestures at the level of the operating system.
Energy systemoptimizationmodeling tools provide insights for the evaluation of energy strategies minimizing the total cost of the integrated supply-demand system. In the classical formulation, costs for the differen...
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ISBN:
(纸本)9798350381757;9798350381740
Energy systemoptimizationmodeling tools provide insights for the evaluation of energy strategies minimizing the total cost of the integrated supply-demand system. In the classical formulation, costs for the different energy technologies are assigned as parameters, withthe possibility to account for cost reductions just depending on elapsed time, independently from the effective rate of adoption of a technology (exogenous learning). this work adopts the TEMOA-Europe model instance to implement a nonlinear endogenous technology learning algorithm. Endogenous learning changes the unit investment cost acting according to assigned learning rates. the case study examined here considers a net-zero emissions scenario by 2050 analyzing the effects of endogenous learning on electricity generation, hydrogen production technologies and cars. the results highlight large differences in the development of those sectors interested by the application of learning rate when comparing the exogenous and the endogenous learning runs, despite negligible effects on the overall system and on the increase in computational cost.
this paper presents a medium-term scheduling model of a hybrid hydro-solar power plant. the study examines how hybridization enhances the security of supply of a hydro-only system, particularly in Nordic weather condi...
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ISBN:
(纸本)9798350381757;9798350381740
this paper presents a medium-term scheduling model of a hybrid hydro-solar power plant. the study examines how hybridization enhances the security of supply of a hydro-only system, particularly in Nordic weather conditions. A stochastic dynamic programming (SDP) algorithm is implemented to properly address the uncertainty of Nordic weather conditions and calculate water values. With solar power modeled as a photovoltaic (PV) installation, a hybrid system was created to optimize the load fulfillment. the results from the hybrid system were compared withthe reference hydro-only system and an energy-upgraded hydro-only system using a creek inlet. the Ormsetfossen power plant, a Norwegian hydropower system with two reservoirs, is used as a reference for the data collection and topology modeling. Scenarios from 30 weather years of inflow and solar irradiation data were used to produce production plans for the hybrid and hydro-only configurations. Results indicate that hybridization enhances the security of supply to a greater extent than the energy-upgraded hydro-only system. the energy-upgraded hydro-only system is on the other hand more self-sufficient and less reliant on power imported from the market.
this paper presents a smart navigation systemthat uses Building Information modeling (BIM) data extracted from Industry Foundation Classes (IFC) files to generate a graph network for efficient path planning. the prop...
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ISBN:
(纸本)9798350319439
this paper presents a smart navigation systemthat uses Building Information modeling (BIM) data extracted from Industry Foundation Classes (IFC) files to generate a graph network for efficient path planning. the proposed method focuses on the construction of a graph networks, and the application of optimization algorithms to estimate optimal paths in a building environment. First, we extract relevant information about the building such as spaces, doors. this data serves to construct a graph network that represents the connectivity and relationships between different spaces in the building. Once the graph network is established, optimization algorithms are used to estimate optimal paths for navigation. the proposed method aims to provide accurate and efficient path recommendations, enhancing navigation in the building environment. the performance of our method is evaluated using a larger graph network derived from a real-world building. the results demonstrate the potential of the smart navigation system in achieving reliable path planning.
this paper presents an optimization framework for a pool comprising a wind-farm and a grid-scale Battery Energy Storage system (BESS). the proposed framework optimizes the day-ahead (D-1) bidding decisions in the day-...
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ISBN:
(纸本)9798350381757;9798350381740
this paper presents an optimization framework for a pool comprising a wind-farm and a grid-scale Battery Energy Storage system (BESS). the proposed framework optimizes the day-ahead (D-1) bidding decisions in the day-ahead energy market and in the Automatic Frequency Restoration Reserve (aFRR) capacity and energy markets, in view of uncertainties pertaining to actual wind power production, aFRR energy activation, as well as aFRR capacity market prices. the aFRR energy activation mechanism follows the architecture of the recently introduced European PICASSO market platform. the model is formulated as a three-stage stochastic optimization problem, modeling explicitly the operational constraints related to the BESS state-of-charge management when providing aFRR. In addition, using the Conditional-Value-at-Risk (CVaR), the proposed framework allows to model different levels of risk aversion. this optimal bidding model is evaluated using actual data, i.e., market prices and wind power production from July to December 2022. the results of our case study showcase the additional revenue streams emerging from the wind-battery joint operation, the wind imbalance mitigation benefits of the BESS and the value of the aFRR capacity and energy markets.
this paper proposes a Matlab framework for the optimized design of mixed-signal accelerator for Deep Neural Networks (DNNs), based on the Flipped (F)-2T2R RRAM compute cell. the manuscript describes an analytical mode...
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In the era of the Edge -to -Cloud Continuum paradigm, effectively managing heterogeneous and distributed resources poses significant challenges. Autonomic system operation, supported by Artificial Intelligence (Al) dr...
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ISBN:
(纸本)9798350369458;9798350369441
In the era of the Edge -to -Cloud Continuum paradigm, effectively managing heterogeneous and distributed resources poses significant challenges. Autonomic system operation, supported by Artificial Intelligence (Al) driven resource management and application deployment mechanisms, offers a promising solution. Machine Learning (NIL) models are pivotal for this purpose, necessitating large amounts of high quality data for training, validation, and evaluation. Simulators play a crucial role by generating vast datasets containing diverse data types, facilitating training, testing, and analyzing ML and Al techniques for autonomic systemoptimization. this paper aims to review existing simulators and identify a candidate simulator suitable for generating datasets within the Edge-to-Cloud Continuum, supporting the development of efficient ML models.
Hydropower systems consist of complex river systems making hydropower modelling computational expensive. the power output of hydropower stations are depending on the efficiency curve of a turbine, the head-height and ...
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ISBN:
(纸本)9798350381757;9798350381740
Hydropower systems consist of complex river systems making hydropower modelling computational expensive. the power output of hydropower stations are depending on the efficiency curve of a turbine, the head-height and the discharge through a turbine. the cascade ordering of reservoirs in river system results in further interdependencies and thus long simulations. Especially when simulating bigger energy system, e.g. the European system, a simplification is required. In earlier research, an "equivalent model" is calculated by using a bi-level optimization problem with a particle swarm optimization (PSO) approach. the principle is to intelligently aggregate plants in one area into an equivalent model that mimics the behavior of the detailed model. Due to the simplifications, the risk of losing interdependencies is high. the equivalent model underestimates production in high price periods, and overestimates in low price periods respectively. this paper combines recently ideas and introduces two new adjustments that improves the equivalent performance.
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