Quantity prediction of municipal solid waste (MSW) is crucial for design and programming municipal solid waste management system (MSWMS). Because effect of various parameters on MSW quantity and its high fluctuation, prediction of generated MSW is a difficult task that can lead to enormous error. The works presented here involve developing an improved support vector machine (SVM) model, which combines the principal component analysis (PCA) technique with the SVM to forecast the weekly generated waste of Mashhad city. In this study, the PCA technique was first used to reduce and orthogonalize the original input variables (data). Then these treated data were used as new input variables in SVM model. This improved model was evaluated by using weekly time series of waste generation (WG) and the number of trucks that carry waste in week of t. These data have been collected from 2005 to 2008. By comparing the predicted WG with the observed data, the effectiveness of the proposed model was verified. Therefore, in authors' opinion, the model presented in this article is a potential tool for predicting WG and has advantages over the traditional SVM model.

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Gas oil gravity drainage is an effective oil recovery process, which has been proven in the field. Under favorable conditions the displacement is stable and for the right surface tension combinations the residual oil saturation is low. In the absence of gas dissolution, the recovery after gas injection is usually low as a large amount of oil remains capillary trapped in the matrix blocks. However, when the main gas constitutes is soluble in the oil, the dissolution leads to mixing and interfacial tension (IFT) reduction, which cause gravity enhanced transfer between matrix and fracture. Therefore, a study of the mechanisms that control the interactions between fracture and matrix (e.g. capillarity, gravity, phase behavior and flow behavior) can help to optimize recovery. This paper concerns an experimental study to investigate whether gravity drainage is also an effective recovery process in fractured reservoirs. In this study, we describe six gas injection experiments conducted at different miscibility conditions, i.e., immiscible, developed miscible and first contact miscible (FCM), using CO 2 , nitrogen and flue gas. In addition, the impact of switching from an immiscible (Nitrogen, Flue gas) injection gas to non-equilibrium and fully miscible CO 2 injection is investigated. In one of the experiments, we study the effect of a permeability barrier on the recovery efficiency from the matrix block when CO 2 is injected in the fracture at immiscible and miscible conditions. Accurate modeling for the transfer between fracture and matrix is also essential for accurate recovery predictions. In this study, a numerical model is developed to perform compositional simulations of gas injection for different miscibility scenarios. Results revealed that ultimate oil recovery increases considerably once miscibility is reached. Miscibility can usually be achieved at high pressures only. High pressure gas injection has two disadvantages, viz., (1) one may need a larger mass of gas to fill the pore space from where the oil is recovered and (2) the density of injected gas increases significantly, which reduces the density difference between the gas and oil. This leads to less effective gravity mediated recovery. Even if the impermeable layer impairs the performance of the gas oil gravity drainage (GOGD) process for immiscible gas injection, it improves the recoveries for first contact miscible gas injection.