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Complementarity-based nonlinear programming techniques for optimal mixing in gas networks
We consider nonlinear and nonsmooth mixing aspects in gas transport optimization problems. As mixed-integer reformulations of pooling-type mixing...
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Support Vector Machine
The more the dimensions of a feature space, the more is the computing power needed to classify. Support vector machines (SVMs) main advantages are...
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VIX Computation Based on Affine Stochastic Volatility Models in Discrete Time
We propose a class of discrete-time stochastic volatility models that, in a parsimonious way, capture the time-varying higher moments observed in...
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COVID-19 and persistence in the stock market: a study on a leading emerging market
In this study, we examine how sectors of the National Stock Exchange from India respond to the uncertainties introduced by the COVID-19 pandemic. By...
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Value of intermediate imaging in adaptive robust radiotherapy planning to manage radioresistance
In radiotherapy, uncertainties in tumor radioresistance and its progression can degrade the efficacy of deterministic treatments. While a robust...
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Executing a business model change: identifying key characteristics to succeed in volatile markets
The world is changing, and with it comes the requirement that enterprises change to survive in today's volatile markets. However, the change does not...
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Understanding the Uncertainty Using Sensitivity Analysis in Artificial Neural Networks
The uncertainty of outcomes with respect to the uncertain inputs is usually explored in sensitivity analysis. In particular, we address in this work...
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The Heath Jarrow Morton Model
This chapter presents the Heath, et al. (Econometrica 60(1):77–105, 1992) model for pricing interest rate derivatives. Given frictionless and...
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Extending the Merton model with applications to credit value adjustment
Following the global financial crisis, the measurement of counterparty credit risk has become an essential part of the Basel III accord with credit...
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Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)
This study provides a holistic and quantitative overview of over 800 mathematical methods (e.g., financial and risk models, statistical tests,...
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Noncooperative Supply Chain Scheduling
This chapter discusses the application of noncooperative solution methods, especially noncooperative game theory, to decentralized supply chain...
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Role of Artificial Intelligence and Deep Learning in Skin Disease Prediction: A Systematic Review and Meta-analysis
Skin is a most essential and extraordinary part of the human structure. Exposure to chemicals such as nitrates, sunlight, arsenic, and UV rays due to...
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Decentralized convex optimization on time-varying networks with application to Wasserstein barycenters
Inspired by recent advances in distributed algorithms for approximating Wasserstein barycenters, we propose a novel distributed algorithm for this...
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Joint throughput-energy optimization in multi-gateway LoRaWAN networks
Nowadays, LoRaWAN has become one of the most widely deployed low-power wide-area technologies suitable for Internet of Things applications. Sensor...
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Constrained Optimization Conditions
We turn now, in this final part of the book, to the study of optimization problems having constraints. We begin by studying in this chapter the...
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Smart network based portfolios
In this article we deal with the problem of portfolio allocation by enhancing network theory tools. We propose the use of the correlation network...
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Proofs of conjectures on the competition between observable and unobservable servers
The impact of information about the quality of service on marketing can be demonstrated by a competition between an observable queue and an...
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Hedging goals
Goal-based investing is concerned with reaching a monetary investment goal by a given finite deadline, which differs from mean-variance optimization...
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Warum man seinen Job (nicht) mögen muss
Seit einigen Jahren kann man einen Wandel in der Motivation und den Bedürfnissen der Arbeitnehmenden feststellen. Die einstige Motivation des reinen...
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A robust optimization approach for repairing and overhauling in a captive repair shop under uncertainty
A robust optimization model is a paradigm for decision-making under uncertainty, where the parameters are given in the form of uncertainty sets. In...
