Random early detection (RED) is an effective active queue management (AQM) algorithm controlling network congestion by average queue length. However, RED is over-sensitive to congestion degrees and its parameters. To ...
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This paper applies the recently developed framework for integral control on nonlinear spaces to two non-standard cases. First, we show that perfect target stabilization in presence of actuation bias holds also if this...
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Deep learning has revolutionized the field of artificial *** on the statistical correlations uncovered by deep learning-based methods,computer vision tasks,such as autonomous driving and robotics,are growing *** being...
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Deep learning has revolutionized the field of artificial *** on the statistical correlations uncovered by deep learning-based methods,computer vision tasks,such as autonomous driving and robotics,are growing *** being the basis of deep learning,such correlation strongly depends on the distribution of the original data and is susceptible to uncontrolled *** the guidance of prior knowledge,statistical correlations alone cannot correctly reflect the essential causal relations and may even introduce spurious *** a result,researchers are now trying to enhance deep learningbased methods with causal *** theory can model the intrinsic causal structure unaffected by data bias and effectively avoids spurious *** paper aims to comprehensively review the existing causal methods in typical vision and visionlanguage tasks such as semantic segmentation,object detection,and image *** advantages of causality and the approaches for building causal paradigms will be *** roadmaps are also proposed,including facilitating the development of causal theory and its application in other complex scenarios and systems.
Coverage optimization is a critical issue in 802.11 Wireless LANs planning problems. In this paper an immune network algorithm named opt-aiNet is studied in order to automatize the planning process by optimizing the B...
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It is well known that feedback failure increases operating errors in control systems. The objective here is to develop controllers that reduce such operating errors in minimal time, once feedback has been restored. It...
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A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Se...
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A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.
The reaction mechanism of chemical process is complex. There is a modeling error between the mechanism model and the actual reaction system. At the same time, there are complex slow time-varying features, such as cata...
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An ethylene plant employs multiple cracking furnaces in parallel to convert various hydrocarbon feedstocks to smaller hydrocarbon molecules. The continuous operational performance of cracking furnaces gradually decays...
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control and regulation of furnace firing is essential to extend the runiength of new and existing furnaces. Accurate Computational Fluid Dynamic simulations of the furnace are essential for this purpose. This requires...
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ISBN:
(纸本)9781510806924
control and regulation of furnace firing is essential to extend the runiength of new and existing furnaces. Accurate Computational Fluid Dynamic simulations of the furnace are essential for this purpose. This requires among others accounting for the detailed geometry of the burners. Also the so-called "shadow effect" 6 arising from the projected shadows between adjacent reactors leads to significant heat flux non-uniformities. This phenomenon is important but its effect on product yields is often ignored as only a single reactor is simulated. For the USC furnace simulated in this work, shadow effects cause a maximum difference in COT of 29 K and a difference in P/E-ratioof 0.1 between two different U-coils in the furnace. In order to obtain more uniform TMT's, COTs and olefin yields for the individual reactors, different furnace optimization methods were compared and their results are discussed. Full furnace CFD simulations prove to be essential in design and during debottlenecking, when aiming for a more uniform COT distribution to the reactors by fuel distribution.
Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthes...
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Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal con figuration and operation conditions of the system. The evolution algorithm and models are interactively used in the calculation, which ensures the feasibility of con figuration and improves computational ef ficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies.
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