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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Bayesian Learning And Predictability In A Stochastic Nonlinear Dynamical Model, John Parslow, Noel Cressie, Edward P. Campbell, Emlyn Jones, Lawrence Murray
Bayesian Learning And Predictability In A Stochastic Nonlinear Dynamical Model, John Parslow, Noel Cressie, Edward P. Campbell, Emlyn Jones, Lawrence Murray
Professor Noel Cressie
Bayesian inference methods are applied within a Bayesian hierarchical modelling framework to the problems of joint state and parameter estimation, and of state forecasting. We explore and demonstrate the ideas in the context of a simple nonlinear marine biogeochemical model. A novel approach is proposed to the formulation of the stochastic process model, in which ecophysiological properties of plankton communities are represented by autoregressive stochastic processes. This approach captures the effects of changes in plankton communities over time, and it allows the incorporation of literature metadata on individual species into prior distributions for process model parameters. The approach is applied …
Stochastic Modeling And Optimization Of Multi-Plant Capacity Planning Problem, Anoop Verma, Nagesh Shukla, S.K Tyagi, Nishikant Mishra
Stochastic Modeling And Optimization Of Multi-Plant Capacity Planning Problem, Anoop Verma, Nagesh Shukla, S.K Tyagi, Nishikant Mishra
Nagesh Shukla
n this paper the problem of capacity planning under risk from demand and price/cost uncertainty of the finished products is addressed. The deterministic model is extended into a two-stage stochastic model with fixed recourse by means of various expected levels of demand as random. A recourse penalty is also included in the objective for both shortage and surplus in the finished products. The model is analyzed to quantify the risk using Markowitz mean-variance model.
Vehicle Routing Problem With Stochastic Demand (Vrpsd): Optimisation By Neighbourhood Search Embedded Adaptive Ant Algorithm (Ns-Aaa), M Nagalakshmi, Mukul Tripathi, Nagesh Shukla, Manoj Tiwari
Vehicle Routing Problem With Stochastic Demand (Vrpsd): Optimisation By Neighbourhood Search Embedded Adaptive Ant Algorithm (Ns-Aaa), M Nagalakshmi, Mukul Tripathi, Nagesh Shukla, Manoj Tiwari
Nagesh Shukla
Taking into account the real world applications, this paper considers a vehicle routing problem with stochastic demand (VRPSD) in which the customer demand has been modelled as a stochastic variable. Considering the computational complexity of the problem and to enhance the algorithm performance, a neighbourhood search embedded adaptive ant algorithm (ns-AAA) is proposed as an improvement to the existing ant colony optimisation. The proposed metaheuristic adapts itself to maintain an adequate balance between exploitation and exploration throughout the run of the algorithm. The performance of the proposed methodology is benchmarked against a set of test instances that were generated using …
Adaptive Stochastic Energy Flow Balancing In Smart Grid, Hassan Shirzeh, Fazel Naghdy, Philip Ciufo, Montserrat Ros
Adaptive Stochastic Energy Flow Balancing In Smart Grid, Hassan Shirzeh, Fazel Naghdy, Philip Ciufo, Montserrat Ros
Dr Philip Ciufo
A smart grid can be considered as an unstructured network of distributed interacting nodes represented by renewable energy sources, storage and loads. The nodes emerge or disappear in a stochastic manner due to the intermittent nature of natural sources such as wind speed and solar irradiation. Prediction and stochastic modelling of electrical energy flow is a critical characteristic in such a network to achieve load balancing and/or peak shaving in order to minimise the fluctuation between off peak and peak demand by power consumers. Before contributing energy to the network, a node acquires information about other nodes in the grid …
Pricing Variance Swaps With Stochastic Volatility, Song-Ping Zhu, Guang-Hua Lian
Pricing Variance Swaps With Stochastic Volatility, Song-Ping Zhu, Guang-Hua Lian
Professor Song-Ping Zhu
Following the pricing approach proposed by Zhu & Lian [19], we present an exact solution for pricing variance swaps with the realized variance in the payoff function being a logarithmic return of the underlying asset at some pre-specified discrete sampling points. Our newly-found pricing formula is based on the Heston's [8] two-factor stochastic volatility model. The discovery of this exact and closed-form solution has significantly improved the computational efficiency involved in computing the value of variance swaps with discrete sampling points.
Stochastic Modelling Of Multi-Grain Equivalent Dose (De) Distributions: Implications For Osl Dating Of Sediment Mixtures, Richard Roberts, Lee Arnold
Stochastic Modelling Of Multi-Grain Equivalent Dose (De) Distributions: Implications For Osl Dating Of Sediment Mixtures, Richard Roberts, Lee Arnold
Richard G Roberts
No abstract provided.