In this paper a design methodology of 'distributed' energy systems is presented. These are defined as energy systems with unregulated distributed generators connected to the lower voltage levels. The cornersto...
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In this paper a design methodology of 'distributed' energy systems is presented. These are defined as energy systems with unregulated distributed generators connected to the lower voltage levels. The cornerstone in their design is the steady-state analysis of distribution systems under uncertainty in energy in energy generation and consumption. Based on this definition, the structure of a system-design tool is proposed. The system is described by the steady-state model, while all different types of distributed generators (dispatchable or nondispatchable technology concepts) are treated in a unifying manner through probabilistic modelling. The modelling of the interdependence between the random input variables is treated by introducing the concepts of comonotonicity, countermonotonicity and independence between distributed generations and distributed consumptions as stochastic bounds describing extreme statistical dependence between the input random variables.
The interaction balance method (IBM) with fuzzy constraints is proposed for large-scale industrial processes under hierarchical steady-state optimization with the consideration of the model-reality difference and the ...
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The interaction balance method (IBM) with fuzzy constraints is proposed for large-scale industrial processes under hierarchical steady-state optimization with the consideration of the model-reality difference and the constraints of subprocesses being flexible. In this approach, the models that are treated as equality constraints and the inequality constraints of the subprocesses are all fuzzified. Two cases of interaction balance method are studied: the open-loop IBM and the IBM with global feedback. Simulation results show that the solutions of the proposed method with global feedback are very close to the optimal solutions of the real process.
Software process components that share information and that cooperate for common tasks lead to multiple problems of interoperability. Some based-interoperability approaches have been proposed. However, more problems r...
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ISBN:
(纸本)9728865007
Software process components that share information and that cooperate for common tasks lead to multiple problems of interoperability. Some based-interoperability approaches have been proposed. However, more problems remain to be solved to enable the heterogeneous process components interoperability at execution level. This paper presents a process-based approach (architecture) for the federation of software process systems. Based on this approach, we focus on its implementation problems for the process execution interoperability. We show how we solve these problems and we discuss their implementation through the main development techniques of distributed applications.
This paper reviews what the first Author and his Group have been investigating for the past decade in the on-line steady-state hierarchical intelligent control and optimization of large-scale industrial processes (LSI...
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This paper reviews what the first Author and his Group have been investigating for the past decade in the on-line steady-state hierarchical intelligent control and optimization of large-scale industrial processes (LSIP), as well as large-scale systems (LSS). The techniques include the use of neural networks for identification and optimization, the use of expert systems to solve some kinds of hierarchical multi-objective optimization problems, the use of the fuzzy logic control and the use of the iterative learning control. In addition, several implementation examples and the product quality control for LSS are introduced. Finally the paper prospects the new stages of development.
In this paper we present the structure of the simulator which would allow diving beginners to experience the effect of buoyancy control mechanisms before actually entering the *** believe such training would be less s...
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The dual data cache is a cache organization with a split temporal/spatial cache. The temporal sub-cache stores data exhibiting temporal locality and the spatial sub-cache saves data exhibiting spatial locality. A loca...
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The dual data cache is a cache organization with a split temporal/spatial cache. The temporal sub-cache stores data exhibiting temporal locality and the spatial sub-cache saves data exhibiting spatial locality. A locality prediction table is used to predict the type of locality load/store instructions exhibit. In this way, both types of locality can be exploited more effectively. Unfortunately, the dual data cache does not make effective use of the entire cache capacity. If most memory references exhibit the same type of locality, only one sub-cache will be used. We therefore propose a cache organization called the Unified Dual Data Cache that employs only one (unified) cache unit. If a cache miss occurs and the locality prediction is temporal, only the missing block is fetched from the next memory level. If on the other hand spatial locality is predicted, adjacent blocks are also brought to the cache. In fact, we present two versions of the UDDC called the UDDC Type A (UDDC-A) and the UDDC Type B (UDDC-B), respectively. The difference between the two types is that in the UDDC-B each smaller block is tagged, while in the UDDC-A the smaller blocks within a larger block share the tag.
A multivalent logic approach to estimating the risk of error on test samples of learning machine is developed and compared to the bivalent approach based on VC dimension, cover and entropy numbers of sets. The multiva...
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A multivalent logic approach to estimating the risk of error on test samples of learning machine is developed and compared to the bivalent approach based on VC dimension, cover and entropy numbers of sets. The multivalent approach leads to more simple expressions for predicting bounds on the risk estimation which are computable in a short time and use a reasonable amount of computer memory. The results of testing reveal that the multivalent logic algorithm outperforms support vector machines.
Theories for a complexity estimation of different learning machines use the Vapnik Chervonenkis dimension, or various approximations to it, to predict optimal structure of a learning machine. This approach has some de...
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Theories for a complexity estimation of different learning machines use the Vapnik Chervonenkis dimension, or various approximations to it, to predict optimal structure of a learning machine. This approach has some deficiencies that stems from Aristotelian logic foundation behind the Vapnik Chervonenkis dimension. An alternative fuzzy logic approach is introduced that brings a concise definition of errors and complexity estimation of a learning machine. In contradiction to the statistical learning theory where errors are actually counted in the fuzzy logic approach errors are measured. It is necessary to include information about the distances of violations about the quality of prediction. Some experiments are presented to evaluate a quality of propose algorithm.
A Java based genetic programming kernel (GPK) is described. Its main features are ease of use, portability, and robustness, which were achieved by strongly using the Java reflection mechanism. This unique characterist...
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A Java based genetic programming kernel (GPK) is described. Its main features are ease of use, portability, and robustness, which were achieved by strongly using the Java reflection mechanism. This unique characteristic of our GPK distinguishes it from other similar frameworks. GPK was successfully used in our research work as well in the teaching process.
The flattening of digitized surfaces is still very important in design of thin walled objects such as the airplane wings, parts of car bodies, textile products, and shoe uppers. Especially in shoe industry, the abilit...
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The flattening of digitized surfaces is still very important in design of thin walled objects such as the airplane wings, parts of car bodies, textile products, and shoe uppers. Especially in shoe industry, the ability of quick respond to changing market needs is essential for successful competition. To give needed flexibility to a shoe designer, special CAD/CAM systems have been developed. Those systems are based on algorithms for surface reconstruction and surface flattening. In this article a fast algorithm for surface reconstruction and surface flattening is presented. Developable stripes are used to approximate a surface. In this way the surface can be flattened fast and without any distortions.
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