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搜索结果: 1-15 共查到Optimization相关记录999条 . 查询时间(0.156 秒)
Quantifying the impact of carbon (C) and timber prices on harvest scheduling and economic returns is essential to define strategies for the sustainable management of short-rotation plantations so that...
Communication compression is an essential strategy for alleviating communication overhead by reducing the volume of information exchanged between computing nodes in large-scale distributed stochastic ...
In the first part, I shall present a new way to construct highly stiff stable schemes. Traditional time discretization schemes are usually based on Taylor expansions at $t_{n+\beta}$ with $\beta\in [0...
As a sort of emerging unconventional energy, shale gas has extensive market outlook by virtue of its enormous reserves, and concerns for shale gas exploitation and processing have been raised nowadays...
TWo significant forms of energy widely used in chemical industries are heat and work related to temperature and pressure manipulation. Since complex relationship exists in these strongly interacting p...
A multiobjective optimization (MOO) framework considering the dual objectives of the economy and the environment is presented in this work for the extended integration of interplant heat exchanger net...
In this article, a novel simulation-optimization method is proposed for the simultaneous design of a heat-integrated coal-to-SNG/MeOH (CTSM) polygeneration process, aiming at exergy efficiency enhance...
A heat exchanger network (HEN) plays an important role in the chemical process industry owing to its significant effect in energy recovery. A compression-absorption cascade refrigeration system (CACRS...
Zigzag-type pore model with a modified structure was proposed to evaluate the effect of micropore structure on the gas separation performance of carbon molecular sieve membranes (CMSM). Molecular simu...
In this talk, we will introduce some optimization problem in remote sensing data processing. The high dimensional characteristics of remote sensing data, especially hyperspectral data, will not only l...
In this talk, we discuss a unifying deep unfolding multi-sampling-ratio interpretable CS-MRI framework. The combined approach offers more generalizability than the existing deep-learning-based CS-MRI ...
We focus on the nonconvex-strongly-convex bilevel optimization problem (BLO). In this BLO, the objective function of the upper-level problem is nonconvex and possibly nonsmooth, and the lower-level pr...
Tensor-based modeling and computation emerge prominently with urgent demands from practical applications in the big data era. With the intrinsic sparsity in real data sets and the dimensionality reduc...
Sparsity is a naturally occurring characteristic in many real-world applications including signal denoising, outlier detection, and finance. On one hand, sparsity assumption allows people to tackle in...
Zero-One Composite Optimization (0/1-COP) is a prototype of nonsmooth, non- convex optimization problems and it has attracted much attention recently. Augmented Lagrangian Method (ALM) has stood out a...

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