Owing to the fact that three-dimensional structures of biological macromolecule determine their functions, the development of prediction approaches of RNA secondary structures is undoubtedly of great significance, whi...
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Owing to the fact that three-dimensional structures of biological macromolecule determine their functions, the development of prediction approaches of RNA secondary structures is undoubtedly of great significance, which becomes one of the most important topics in the field of computational biology. On the basis of the analysis of dynamicprogramming method involved in RNA secondary structure predictions, a new RNA prediction approach was presented using fuzzy dynamic programming. The optimal fuzzy folding problem of tRNA families of the E. coli genome sequence was considered. A collection of fuzzy parameters such as fuzzy decisions, fuzzy goals, states, and fuzzy termination times were given. Based on the RNAfold module in the ViennaRNA package, the new RNA prediction algorithm was implemented, in which any possible secondary structures were generated when tRNA sequences of E. coli are used as an input. Furthermore, the alaT tRNA sequence of E. coli as a test sample was used and four fuzzy predictions of possible secondary structures were produced. All these results were visualized and analyzed.
This paper aims to develop a fuzzy dynamic programming approach for multiobjective multistage decision making problems. fuzzy dynamic programming usually convert the problems into corresponding single objective proble...
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This paper aims to develop a fuzzy dynamic programming approach for multiobjective multistage decision making problems. fuzzy dynamic programming usually convert the problems into corresponding single objective problems by an aggregate of hybrid objective values that expresses the performance of the particular stage decision. Weight-assessment is an important problem arising from the evaluation of multiple objectives. Therefore, a fuzzy iteration model is first developed to simultaneously provide the objective weights and the evaluation of alternatives with multiple objectives. Then a fuzzy dynamic programming is derived by applying the fuzzy iteration model to classic dynamicprogramming to evaluate the decisions at each stage in the dynamic process of decision makings, where the objective weights are initially elicited from the information implicit in alternatives and can be interactively adjusted to reflect the changes of decision situations by using a non-structured decision making analysis method if necessary. Finally, the fuzzy dynamic programming is validated through a problem of water resource allocation. (c) 2004 Elsevier B.V. All rights reserved.
This paper deals with an optimal stopping problem in dynamicfuzzy systems with fuzzy rewards, and shows that the optimal discounted fuzzy reward is characterized by a unique solution of a fuzzy relational equation. W...
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This paper deals with an optimal stopping problem in dynamicfuzzy systems with fuzzy rewards, and shows that the optimal discounted fuzzy reward is characterized by a unique solution of a fuzzy relational equation. We define a fuzzy expectation with a density given by fuzzy goals and we estimate discounted fuzzy rewards by the fuzzy expectation. This paper characterizes the optimal fuzzy expected value and gives an optimal stopping time.
Various forms of disasters, natural and man-made, abound. Although, to some extent, some of these have been exacerbated by modern civilization, various technologies have been invoked to control or mitigate their adver...
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Various forms of disasters, natural and man-made, abound. Although, to some extent, some of these have been exacerbated by modern civilization, various technologies have been invoked to control or mitigate their adverse effects. Modeling- and optimization-based techniques have also been employed. We outline some efforts based on fuzzy sets theory which are utilized in conjunction with classical methods to enhance the reliability and utility of these efforts. In particular, disasters caused by floods and storm water pollution are used as vehicles for the exemplification of our models.
This paper presents a novel adaptive control strategy for integrating direct load control (DLC) with interruptible load management (ILM) to provide instantaneous reserves for ancillary services in deregulated power sy...
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This paper presents a novel adaptive control strategy for integrating direct load control (DLC) with interruptible load management (ILM) to provide instantaneous reserves for ancillary services in deregulated power systems. fuzzy dynamic programming is used to satisfy customers' requirements and yields a near optimal pre-scheduling of the DLC. Then, the energy payback associated with the DLC is further eliminated by the adaptive control strategy, which exploits interruptible loads to modify the DLC schedule in real-time. Through the developed adaptive control strategy, the influences of the load uncertainties and forecasting errors on the pre-scheduling of the DLC can also be excluded. The proposed algorithm was practically tested on the Taiwan power (Taipower) 38-unit system with 20 air-conditioner loads and 15 interruptible loads. The outcomes reveal that an exact amount of instantaneous reserves can be successfully acquired, and the results are robust against dynamic disturbances of the power system.
A new approach using fuzzy dynamic programming for generator maintenance scheduling in power systems is proposed. In this paper, multiple objectives and soft constraints are expressed by fuzzy sets. The process of sol...
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A new approach using fuzzy dynamic programming for generator maintenance scheduling in power systems is proposed. In this paper, multiple objectives and soft constraints are expressed by fuzzy sets. The process of solution formulation is discussed. A practical example chosen from Taiwan Power Company is tested and demonstrated in this paper. Operation experts are consulted for the determination of membership functions. Test solutions prove the capability and effectiveness of this approach to solve the generator maintenance scheduling problem.
This paper presents a model reference adaptive control (MRAC) strategy for interruptible load management (ILM). The proposed MRAC strategy consists of fuzzy dynamic programming (FDP) and priority-based heuristics infe...
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This paper presents a model reference adaptive control (MRAC) strategy for interruptible load management (ILM). The proposed MRAC strategy consists of fuzzy dynamic programming (FDP) and priority-based heuristics inference rule (PBHIR) to offer a flexible solution and a real-time adjusting scheme for the ILM problem. The customers' requirements can be dealt with by the fuzzy variables, and the optimal or near optimal schedule of interrupted load can be acquired through DP search scheme. Additionally, a PBHIR is further employed as a regulator for the MRAC to modulate the schedule of the interrupted load in real time. The influences of the load variations and forecasting errors on the outputs of the FDP can be eliminated by the MRAC. The proposed MRAC strategy is tested practically on the Dar-Gun substation in Taiwan power (Taipower) system. The test results demonstrate the feasibility and effectiveness of applying the proposed method to the ILM problem.
This work presents a model to evaluate the Distribution System dynamic De-adaptation respecting its planning for a given period of Tariff Control. The starting point for modeling is brought about by the results from a...
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This work presents a model to evaluate the Distribution System dynamic De-adaptation respecting its planning for a given period of Tariff Control. The starting point for modeling is brought about by the results from a multi-criteria method based on fuzzy dynamic programming and on Analytic Hierarchy Processes applied in a mid/short-term horizon (stage 1). Then, the decision-making activities using the Hierarchy Analytical Processes will allow defining, for a Control of System De-adaptation (stage 2). a Vector to evaluate the System dynamic Adaptation. It is directly associated to an eventual series of inbalances that take place during its evolution. (C) 2009 Elsevier Ltd. All rights reserved.
This paper gives analytical approaches and algorithms for decision tree search techniques. The decision trees are assumed to have a fixed number of stages and predefined possible states at every stage. The costs of tr...
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This paper gives analytical approaches and algorithms for decision tree search techniques. The decision trees are assumed to have a fixed number of stages and predefined possible states at every stage. The costs of traversing the tree are characterized as approximate and defined as fuzzy numbers. Two search methods, each drawing from an existing non-fuzzy search algorithm, are described. The first method is a dynamicprogramming search, where the principle of optimality with fuzzy costs is addressed. The second method is an A* search for which the notion of a lower bound estimate of costs is utilized to increase the efficiency of the search. Algorithms for each method are included. Theorems and proofs which complete the analytical development of these techniques are also included. Finally, a numerical example illustrating the procedure is given.
In this paper, a new approach using fuzzy dynamic programming is proposed for solving the multiple criteria resource allocation problems, It has been concluded that solutions obtained by this approach are always effic...
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In this paper, a new approach using fuzzy dynamic programming is proposed for solving the multiple criteria resource allocation problems, It has been concluded that solutions obtained by this approach are always efficient, hence an ''optimal'' compromise solution can be introduced. A characteristic feature of the presented approach is that the objective function (scalarization) can be taken into account by using fuzzy set notations. A numerical example is given to clarify the developed approach.
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