Search results for " optimization"
showing 10 items of 2367 documents
Optimal design of viscoelastic tuned mass dampers for structures exposed to coloured excitations
2022
Dynamic interaction between primary and secondary structures can alter the response of buildings, bridges and other civil engineering structures to external stressors such as earthquakes and windstorms. TMDs (tuned mass dampers) are a well-known example of passive control devices that exploit this concept. A TMD consists of a secondary mass attached to the primary structure through a linear or nonlinear link. Various formulations exist to optimize the performance of TMDs, depending on the chosen criterion. Typically, the TMD is optimized considering the steady-state amplitude of motion of the primary structure, e.g., when subjected to monochromatic harmonic excitation (H∞ criterion) or whit…
Electronic structure of tetraphenyldithiapyranylidene : A valence effective Hamiltonian theoretical investigation
1992
We present a theoretical investigation of the electronic structure of tetraphenyldithiapyranylidene (DIPSΦ4) using the nonempirical valence effective Hamiltonian (VEH) method. Molecular geometries are optimized at the semiempirical PM3 level which predicts an alternating nonaromatic structure for the dithiapyranylidene (DIPS) framework. The VEH one‐electron energy level distribution calculated for DIPSΦ4 is presented as a theoretical XPS simulation and is analyzed by comparison to the electronic structure of its molecular components DIPS and benzene. The theoretical VEH spectrum is found to be fully consistent with the experimental solid‐state x‐ray photoelectron spectroscopy (XPS) spectrum…
Optimizing the Performance of Data Warehouse by Query Cache Mechanism
2022
Fast access of data from Data Warehouse (DW) is a need for today’s Business Intelligence (BI). In the era of Big Data, the cache is regarded as one of the most effective techniques to improve the performance of accessing data. DW has been widely used by several organizations to manage data and use it for Decision Support System (DSS). Many methods have been used to optimize the performance of fetching data from DW. Query cache method is one of those methods that play an effective role in optimization. The proposed work is based on a cache-based mechanism that helps DW in two aspects: the first one is to reduce the execution time by directly accessing records from cache memory, and th…
A Spatio-temporal Probabilistic Model of Hazard and Crowd Dynamics in Disasters for Evacuation Planning
2013
Published version of a chapter in the book: Recent Trends in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-38577-3_7 Managing the uncertainties that arise in disasters – such as ship fire – can be extremely challenging. Previous work has typically focused either on modeling crowd behavior or hazard dynamics, targeting fully known environments. However, when a disaster strikes, uncertainty about the nature, extent and further development of the hazard is the rule rather than the exception. Additionally, crowd and hazard dynamics are both intertwined and uncertain, making evacuation planning extremely difficult. To address this chal…
A Sequential Quadratic Programming Method for Volatility Estimation in Option Pricing
2006
Our goal is to identify the volatility function in Dupire's equation from given option prices. Following an optimal control approach in a Lagrangian framework, we propose a globalized sequential quadratic programming (SQP) algorithm with a modified Hessian - to ensure that every SQP step is a descent direction - and implement a line search strategy. In each level of the SQP method a linear-quadratic optimal control problem with box constraints is solved by a primal-dual active set strategy. This guarantees L^1 constraints for the volatility, in particular assuring its positivity. The proposed algorithm is founded on a thorough first- and second-order optimality analysis. We prove the existe…
A Comparison of Multi-objective Algorithms for the Automatic Design Space Exploration of a Superscalar System
2013
In today’s computer architectures the design spaces are huge, thus making it very difficult to find optimal configurations. One way to cope with this problem is to use Automatic Design Space Exploration (ADSE) techniques. We developed the Framework for Automatic Design Space Exploration (FADSE) which is focused on microarchitectural optimizations. This framework includes several state-of-the art heuristic algorithms.
Solving Stochastic Nonlinear Resource Allocation Problems Using a Hierarchy of Twofold Resource Allocation Automata
2010
In a multitude of real-world situations, resources must be allocated based on incomplete and noisy information. However, in many cases, incomplete and noisy information render traditional resource allocation techniques ineffective. The decentralized Learning Automata Knapsack Game (LAKG) was recently proposed for solving one such class of problems, namely the class of Stochastic Nonlinear Fractional Knapsack Problems. Empirically, the LAKG was shown to yield a superior performance when compared to methods which are based on traditional parameter estimation schemes. This paper presents a completely new online Learning Automata (LA) system, namely the Hierarchy of Twofold Resource Allocation …
High-Speed Machines: Typologies, Standards, and Operation under PWM Supply
2018
This paper presents an overview of the most recent state of the art in the field of high-speed electric machines fed through high-frequency converters. This type of systems is rapidly wide spreading in aeronautical and automotive applications, as well as microturbines. Each typology has its own advantages and downsides, which are analytically presented in this paper. Some types of high-speed electric machines require high-frequency voltage supply, highly stressing the dielectric materials of the winding insulation system. For this reason, in high-speed electric drives, premature failure may occur and a reduction of the total system reliability has been observed in the past years. Such issue…
Mapping discounted and undiscounted Markov Decision Problems onto Hopfield neural networks
1995
This paper presents a framework for mapping the value-iteration and related successive approximation methods for Markov Decision Problems onto Hopfield neural networks, for both discounted and undiscounted versions of the finite state and action spaces. We analyse the asymptotic behaviour of the control sets and we give some estimates on the convergence rate for the value-iteration scheme. We relate the convergence properties on an energy function which represents the key point in mapping Markov Decision Problems onto Hopfield networks. Finally, an application from queueing systems in communication networks is taken into consideration and the results of computer simulation of Hopfield netwo…
Robust Ergonomic Virtual Design
2009
Since early development phases of a new industrial product, realistic simulations can be performed in virtual environment to study the human-machine interaction. In a virtual lab it is possible to make experiments to assess the ergonomics of the new product with manikins simulating the human body, and dealing with the problem of anthropometrical variation. Although such sophisticated tools are available, there is still need of a methodo-logical framework aimed at efficiently organizing the experiments in virtual lab. This paper provides an overview of the Robust Ergonomic Virtual Design (REVD), a methodology developed by the authors in the course of the last years. It allows obtaining produ…