In a general Hilbert framework, we consider continuous gradient-like dynamical systems for constrained multiobjective optimization involving non-smooth convex objective functions. Based on the Yosida regularization of the subdifferential operators involved in the system, we obtain the existence of strong global trajectories. We prove a descent property for each objective function, and the conve...

In this paper we suggest an approach for solving a multiobjective stochastic linear programming problem with normal multivariate distributions. Our is combination between method and nonconvex technique. The first transformed into deterministic introducing the expected value criterion utility function that represents decision makers preferences. obtained reduced to mono-objective quadratic using...

In this paper a hierarchical classification framework using the feature-weighting tree for the objective of applying diverse weighting to acoustic features is proposed for speech recognition. The hierarchical feature-weighting tree with a flexible structure complexity can be constructed optimally with the optimal splitting for the recognition confusion graph. Based on the minimum classification...

The paper presents a new variant of parameter estimation methods for discrete hidden Markov models(HMM) in speech recognition. This method makes use of a codeword dependent distribution normalization(CDDN) and a distance weighting by fuzzy contribution in dealing with the problems of robust state modeling in a FVQ based modeling. The proposed method is compared with the existing techniques usin...

In this paper, we propose a multi-objective traffic engineering scheme using different distribution trees to multicast several flows. The aim is to combine into a single aggregated metric, the following weighting objectives: the maximum link utilization, the hop count, the total bandwidth consumption, and the total end-to-end delay. Moreover, our proposal solves the traffic split ratio for mult...

We propose a new algorithm to induce inversion transduction grammars, in which a crosslingual semantic frame based objective function is injected as confidence weighting in the early stages of statistical machine translation training. Unlike recent work on improving translation adequacy that uses a monolingual semantic frame based objective function to drive the tuning of loglinear mixture weig...

fractured reservoirs contain about 85 and 90 percent of oil and gas resources respectively in iran. acomprehensive study and investigation of fractures as the main factor affecting fluid flow or perhapsbarrier seems necessary for reservoir development studies. high degrees of heterogeneity andsparseness of data have incapacitated conventional deterministic methods in fracture networkmodeling. r...

We generalize the Allais common consequence effect by describing three common consequence effect conditions and characterizing their implications for the probability weighting function in rank-dependent expected utility. The three conditions—horizontal, vertical, and diagonal shifts within the probability triangle—are necessary and sufficient for different curvature properties of the probabilit...