A new projection-based neural network for constrained variational inequalities.

This paper presents a new neural network model for solving constrained variational inequality problems by converting the necessary and sufficient conditions for the solution into a system of nonlinear projection equations. Five sufficient conditions are provided to ensure that the proposed neural network is stable in the sense of Lyapunov and converges to an exact solution of the original problem by defining a proper convex energy function. The proposed neural network includes an existing model, and can be applied to solve some nonmonotone and nonsmooth problems.

[Chelating stabilization of heavy metals in fly ash from municipal solid waste incinerators for co-disposal in sanitary landfill].

The characteristics and leaching behavior of heavy metals in fly ash, sampled from 4 MSWI plants, were investigated in this study. The results indicated that the main elements of fly ash were Si, Ca, Al, Cl, and heavy metals such as lead, zinc, copper, chromium and cadmium were enriched in fly ash which had great environmental risk. However, co-disposal of fly ash in sanitary landfill was an available and practical resolvent.

[Characterization and heavy metals leaching toxicity of fly ash from municipal solid waste incinerators in China].

The characteristics and leaching behavior of heavy metals in fly ash, sampled from 12 MSWI plants in China, were investigated. The results indicated that the main elements of fly ash were Si, Ca, Al, Fe, K, Na, Cl, and the total fraction of heavy metals was in the range of 0.5 % - 3.

[Extraction procedure for leaching toxicity of fly ash from municipal solid waste incinerators under Co-disposal scenario in landfill].

The behavior of acidity neutralization capacity (ANC) depletion and change of pH values in leachate from two representative samples were investigated with test of general acidity neutralization capacity (GANC) and multistage extraction test (MET). The results indicated that low estimation of potential environmental risk would be conduced with low depletion of ANC and high pH values of leachate in such actual batch test. Comparing the results of GANC with that of MET, neutralization and wash-out process would take place at the same way under the flow-through scenarios of co-disposal, and there is one-third alkaline components reacting in the neutralization process.

A high-performance feedback neural network for solving convex nonlinear programming problems.

Based on a new idea of successive approximation, this paper proposes a high-performance feedback neural network model for solving convex nonlinear programming problems. Differing from existing neural network optimization models, no dual variables, penalty parameters, or Lagrange multipliers are involved in the proposed network. It has the least number of state variables and is very simple in structure.

Exponential stability of globally projected dynamic systems.

In this paper, we further analyze and prove the stability and convergence of the dynamic system proposed by Friesz et al.(1994), whose equilibria solve the associated variational inequality problems. Two sufficient conditions are provided to ensure the asymptotic stability of this system with a monotone and asymmetric mapping by means of an energy function.

[PCDD/Fs distribution in MSWI fly ash and identification of the indicated isomer].

Four municipal solid waste incinerator (MSWI) fly ash samples were analyzed for PCDD/Fs. The toxicity equivalent quotient (TEQ) was 0.34 - 3.

A novel neural network for variational inequalities with linear and nonlinear constraints.

Variational inequality is a uniform approach for many important optimization and equilibrium problems. Based on the sufficient and necessary conditions of the solution, this paper presents a novel neural network model for solving variational inequalities with linear and nonlinear constraints. Three sufficient conditions are provided to ensure that the proposed network with an asymmetric mapping is stable in the sense of Lyapunov and converges to an exact solution of the original problem.

[Distribution and characters of heavy metals from municipal solid waste incinerator fly ash].

The distribution and characters of heavy metals from municipal solid waste incinerator fly ash was studied in East China. The result indicate that heavy metals in fly ash were mainly distributed in fine particles. The heavy metals including Cd, Pb, Mg, and Cu could migrate easily from fly ash while Ag and Sn would be more stable.

A neural network for a class of convex quadratic minimax problems with constraints.

In this paper, we propose a neural network for solving a class of convex quadratic minimax problems with constraints. Four sufficient conditions are provided to ensure the asymptotic stability of the proposed network. Furthermore, the exponential stability of the proposing network is also proved under certain conditions.

A novel neural network for nonlinear convex programming.

In this paper, we present a neural network for solving the nonlinear convex programming problem in real time by means of the projection method. The main idea is to convert the convex programming problem into a variational inequality problem. Then a dynamical system and a convex energy function are constructed for resulting variational inequality problem.

Neural networks for nonlinear and mixed complementarity problems and their applications.

This paper presents two feedback neural networks for solving a nonlinear and mixed complementarity problem. The first feedback neural network is designed to solve the strictly monotone problem. This one has no parameter and possesses a very simple structure for implementation in hardware.