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A novel granular decomposition based predictive modeling framework for cryptocurrencies' prices forecasting

CHINA FINANCE REVIEW INTERNATIONAL 2024年第4期14卷 759-790页

作者： Ghosh, Indranil Jana, Rabin K. Sharma, Dinesh K. Inst Management Technol IT & Analyt Area Hyderabad Telangana India Indian Inst Management Raipur Operat & Quantitat Methods Area Raipur India Univ Maryland Eastern Shore Dept Business Management & Accounting Princess Anne MD USA

PurposeOwing to highly volatile and chaotic external events, predicting future movements of cryptocurrencies is a challenging task. This paper advances a granular hybrid predictive modeling framework for predicting the future figures of Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Stellar (XLM) and Tether (USDT) during normal and pandemic ***/methodology/approachInitially, the major temporal characteristics of the price series are examined. In the second stage, ensemble empirical mode decomposition (EEMD) and maximal overlap discrete wavelet transformation (MODWT) are used to decompose the original time series into two distinct sets of granular subseries. In the third stage, long- and short-term memory network (LSTM) and extreme gradient boosting (XGB) are applied to the decomposed subseries to estimate the initial forecasts. Lastly, sequential quadratic programming (SQP) is used to fetch the forecast by combining the initial *** performance assessment and the outcome of the Diebold-Mariano's pairwise statistical test demonstrate the efficacy of the suggested predictive framework. The framework yields commendable predictive performance during the COVID-19 pandemic timeline explicitly as well. Future trends of BTC and ETH are found to be relatively easier to predict, while USDT is relatively difficult to ***/valueThe robustness of the proposed framework can be leveraged for practical trading and managing investment in crypto market. Empirical properties of the temporal dynamics of chosen cryptocurrencies provide deeper insights.

关键词： Analytics Forecasting Cryptocurrency Long and short-term memory network sequential quadratic programming

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Efficient Modal Design Variables for Optimization of Aero-Elastic Wing

Efficient Modal Design Variables for Optimization of Aero-El...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Poole, D. J. Allen, C. B. Rendall, T. C. S. Univ Bristol Dept Aerosp Engn Bristol BS8 1TR Avon England

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Efficient multi-disciplinary optimization is presented for aero-structural wing optimization using efficient low-dimensional modal design variables. Orthogonal aerofoil design variables are derived in the geometric space via singular value decomposition. Orthogonality of design variables leads to a well-conditioned design space and encourages positive optimizer convergence. These are applied in a sectional fashion for fixed planform drag minimization of a flexible transonic wing. Shock-free solutions are demonstrated for the rigid wing, indicating suitability of the aerofoil modes for sectional-based wing optimization. However, these wings have poor performance when deformed under flight loads, hence full aeroelastic performance is taken into account. Encouragingly, shock-free solutions are again found. Loading is shifted outboard, leading to increased tip-deflection. Monotonic improvement in objective with increase in dimensionality is also observed.

关键词： Aerofoil Singular Value Decomposition Rigid Wings Aerodynamic Shape Optimization sequential quadratic programming Computational Fluid Dynamics Aerodynamic Performance Structural Modeling Aircraft Wing Design Structural Response

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Real Time Powered Descent Guidance Algorithm for Mars Pinpoint Landing with Inequality Constraints

Real Time Powered Descent Guidance Algorithm for Mars Pinpoi...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Swaminathan, Shriram Rajeev, U. P. Ghose, Debasish Indian Space Res Org Guidance Design Div Trivandrum Kerala India Indian Space Res Org Control & Guidance Design Grp Trivandrum Kerala India Indian Inst Sci Aerosp Engn Dept Bangalore Karnataka India

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Real time trajectory optimization of the powered descent phase in Mars pinpoint landing is presented in this paper. The optimal soft landing trajectory in the presence of large initial condition dispersion and inequality constraints on thrust, orientation and path is generated in real time. The guidance algorithm proposed in this paper can converge from a wide range of initial conditions within the capability of the propulsion system (propellant available and thrust). A two level optimization scheme is adopted for solving the trajectory parameters and optimizing fuel consumption. In the outer loop, the required burn duration is iterated using a simple optimization procedure for minimizing fuel consumption. In the inner loop, the trajectory for a given burn time obtained from the outer loop, is solved using a modified Newton-Raphson scheme in the pseudo-spectral global collocation framework. An important advantage of this scheme is that, it does not use any general gradient-based optimization procedures which are time consuming. This makes it attractive for on-board implementation. The algorithm is least sensitive to initial guess values while exhibiting very good convergence properties. The computation cost for solving the trajectory equations is also minimal in terms of optimization time. It is tested for robustness with respect to both initial guess and initial condition dispersion in the Monte Carlo sense.

关键词： Powered Descent Guidance Propellant Trajectory Optimization Fuel Consumption Guidance Algorithms Soft Landing Trajectories Propulsion System sequential quadratic programming Monte Carlo Simulation Pseudo Spectral Method

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Multi-fidelity efficient global optimization: Methodology and application to airfoil shape design

Multi-fidelity efficient global optimization: Methodology an...

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AIAA Aviation Forum and Exposition

作者： Meliani, Mostafa Bartoli, Nathalie Lefebvre, Thierry Bouhlel, Mohamed-Amine Martins, Joaquim R. R. A. Morlier, Joseph Univ Toulouse ISAE SUPAERO Toulouse France Univ Toulouse DTIS ONERA Informat Proc & Syst Dept Toulouse France Univ Michigan Dept Aerosp Engn Ann Arbor MI 48109 USA Univ Toulouse Inst Clement Ader ISAE SUPAERO CNRS Toulouse France

ISBN: (数字)9781624105890

ISBN: (纸本)9781624105890

Predictions and design engineering decisions can be made using a variety of information sources that range from experimental data to computer models. These information sources could consist of different mathematical formulations, different grid resolutions, different physics, or different modeling assumptions that simplify the problem. This leads to information sources with varying degrees of fidelity, each with an associated accuracy and querying cost. In this paper, we propose a novel and flexible way to use multi-fidelity information sources optimally in the context of airfoil shape optimization using both Xfoil and ADflow. The new developments are based on Bayesian optimization and kriging metamodeling and allow the aerodynamic optimization to be sped up. In a constrained optimization example with 15-design variables problem, the proposed approach reduces the total cost by a factor of two compared to a single Bayesian based fidelity optimization and by a factor of 1.5 compared to sequential quadratic programming.

关键词： Airfoil Databases Aerodynamic Shape Optimization Surrogate Model Shape Optimization Probability Density Functions Bayesian Optimization Reynolds Averaged Navier Stokes sequential quadratic programming Black Box Singular Value Decomposition

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An Intelligent Scatter Search (ISS) Algorithm for Scheduling of Charging a Single EV 6

An Intelligent Scatter Search (ISS) Algorithm for Scheduling...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (IEEE PES APPEEC)

作者： Mao, Tian Lau, W. H. Shum, Chong Chung, Henry Tsang, K. F. Tse, Norman C. F. City Univ Hong Kong Ctr Smart Energy Convers & Utilizat Res Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781479975372

Electric vehicles (EVs) becomes popular for energy saving and environmental protection in light of sustainable development in recent years. The wide spread popularity of EVs relies on an effective strategy for charging the battery. Hence, efficient and robust algorithms are essential for implementing the charging strategies. In this paper, an intelligent scatter search (ISS) framework utilizing filter-SQP (sequential quadratic programming) and mixed-integer SQP techniques as local solvers is proposed for handling EV charging with either flexible or constant charging power under both V2G and G2V support. Simulations have been carried out to verify the effectiveness of the proposed ISS algorithm. The results demonstrated that its performance is better than other approaches including GS (global search), GA (genetic algorithm), PSO (particle swarm optimization), and SS/F (scatter search algorithm with local solver fmincon). In addition, its computational load is rather low in regulating the EV charging and thus is very suitable to minimize the operation cost for EV owners.

关键词： Bidirectional and unidirectional charging Charging cost Electric vehicle sequential quadratic programming Scatter search

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Multiple Vehicles Merging Control via Sequence and Trajectory Optimization 4th

Multiple Vehicles Merging Control via Sequence and Trajector...

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4th International Conference on Cognitive Systems and Information Processing (ICCSIP)

作者： Tang, Wei Yang, Ming Qian, Qiyang Wang, Chunxiang Wang, Bing Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Univ Tokyo Sch Engn Tokyo 1138654 Japan

ISBN: (纸本)9789811379864;9789811379857

In multi-lane traffic scenarios, accidents, construction, and other conditions will reduce the number of lanes, and vehicles need to decelerate, merge and pass. Therefore, vehicles merging is a hot topic in multi-vehicle cooperative driving. The existing primary methods focus on merging trajectory optimization based on the known sequence of merging and mainly consider the longitudinal model. Simulated annealing algorithm combined with sequential quadratic programming is used to optimize the merging sequence and the corresponding trajectories. Numerical simulation verifies the stability and feasibility of the algorithm. Finally, the micro intelligent vehicles based simulation platform is introduced to carry out the merging experiment which proves the effectiveness of the proposed algorithm.

关键词： Merging Simulated annealing algorithm sequential quadratic programming

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Fuel-Optimal Guidance for End-to-End Human-Mars Entry, Powered-Descent, and Landing Mission

Fuel-Optimal Guidance for End-to-End Human-Mars Entry, Power...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Wan, Changhuang Jing, Gangshan Dai, Ran Rea, Jeremy R. Ohio State Univ Mech & Aerosp Engn Dept Columbus OH 43210 USA NASA Johnson Space Ctr Flight Mech & Trajectory Design Branch 2001 Nasa Pkwy EG5 Houston TX 77058 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

This paper investigates the fuel-optimal guidance problem of the end-to-end human-Mars entry, powered descent, and landing (EDL) mission. It proposes a computationally efficient modeling scheme and a new optimization algorithm to solve the multi-phase optimal guidance problem. We first model the end-to-end EDL guidance problem as a multi-phase optimal control problem with different dynamics and constraints at each phase. Via polynomial approximation and discretization techniques, this multi-phase optimal control problem is then reformulated as a polynomial programming problem. By introducing intermediate variables and quadratic equality constraints, a polynomial program is equivalently converted into a nonconvex quadratically constrained quadratic program (QCQP). To efficiently solve the large scale QCQPs, a customized alternating direction method of multipliers (ADMM) is designed to search a local optimum. The fuel savings under the end-to-end human-Mars EDL guidance is verified by comparing to the fuel consumption amount using the separate phase guidance approach. Furthermore, the computational efficiency of the customized ADMM algorithm is validated by comparing to the state-of-art nonlinear programming method.

关键词： Fuels Numerical Optimization Bang Bang Control Fuel Consumption sequential quadratic programming Dynamic Pressure Flight Path Angle Aerodynamic Force Hypersonic Inflatable Aerodynamic Decelerator Lagrange Multipliers

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Optimal Overcurrent Relay Coordination in Distribution System using Nonlinear programming Method 2

Optimal Overcurrent Relay Coordination in Distribution Syste...

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IEEE International Conference on Electrical Power and Energy Systems (ICEPES)

作者： Korde, Pragati N. Bedekar, Prashant P. GH Raisoni Inst Engn & Technol Elect Engn Dept Pune Maharashtra India Govt Coll Engn Elect Engn Dept Amravati India

ISBN: (纸本)9781509024766

A simple but powerful optimization method for coordination of over current (OC) relays is presented in this paper. For distribution system protection as well as backup protection in transmission system, overcurrent relay is most widely used. Maloperation of relays may occur if primary and backup relays are not properly coordinated. And therefore relay coordination become important part of power system protection. The main contribution of this paper is application of sequential quadratic programming (SQP) method for calculating optimum values of time multiplier setting (TMS) and plug setting (PS) of OCRs. The proposed algorithm was successfully tested on different systems. Comparison of results with genetic algorithm is also presented in this paper. From results it is found that SQP method is superior as compared to GA technique.

关键词： Overcurrent relay coordination backup protection nonlinear constrained optimization sequential quadratic programming genetic algorithm

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Comparison of Wind Farm Layout Optimization Results Using a Simple Wake Model and Gradient-Based Optimization to Large-Eddy Simulations

Comparison of Wind Farm Layout Optimization Results Using a ...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Thomas, Jared J. Annoni, Jennifer Fleming, Paul Ning, Andrew Brigham Young Univ Dept Mech Engn 360 EB Provo UT 84602 USA Natl Renewable Energy Lab Natl Wind Technol Ctr 15013 Denver West Pkwy Golden CO 80401 USA

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

The models used during wind farm layout optimization use simplifying assumptions that can alter the design space. Some characteristics of the simple models may negatively influence the resulting layouts. In this paper, we perform wind farm layout optimization using a simple wake model and compare the resulting improvements to large-eddy simulation (LES) results to confirm that the layout was actually improved. We begin by describing the models used, including changes specific for use with gradient-based optimization. We then compare our models' output to previously published model and LES results. Using the models described, we performed gradient-based wind farm layout optimization using exact gradients. Power production for the original and optimized layouts were recalculated using LES. The model and LES results were then compared. The simple models predicted an improvement in annual energy production (AEP) of 7.4%, while the LES reported an AEP improvement of 9.9%. We concluded that the improvements found by optimizing with the simple models are not just an artifact of the model characteristics, but are real improvements.

关键词： Large Eddy Simulation Energy Production Wind Turbine Wakes Turbulence Intensity sequential quadratic programming Linear Interpolation Gradient Free Optimization Actuator Disk Wind Tunnel Tests Sparse Nonlinear Optimizer

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Application of Subdivision Surfaces to Aerodynamic Wing Shape Optimisation

Application of Subdivision Surfaces to Aerodynamic Wing Shap...

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AIAA Aviation Forum and Exposition

作者： Kedward, Laurence J. Allen, C. B. Rendall, T. C. S. Univ Bristol Dept Aerosp Engn Bristol BS8 1TR Avon England Univ Bristol Dept Aerosp Engn Computat Aerodynam Bristol BS8 1TR Avon England

ISBN: (数字)9781624105890

ISBN: (纸本)9781624105890

Subdivision surfaces, which generalise tensor-product splines to arbitrary topology, are seeing increased interest in engineering applications. Significantly, the topological flexibility of such subdivision splines enables truly watertight parametric geometry. Previous work by the authors has performed progressive and adaptive shape optimisation using hierarchies of subdivision control fidelities. Such multilevel methods typically enable both global and local shape modifications to occur. In this paper, theory and preliminary results are presented for the application of subdivision surfaces to the aerodynamic optimisation of a modern transport wing. Spline-like control nets are generated from the discretised surface of the wing geometry and used as shape control within a gradient-based aerodynamic shape optimisation framework. A multiresolution formulation ensures that the exact surface is reproduced by the subdivision shape control while also allowing control at varying fidelity. Gradient-based optimisation is performed using an efficient SQP implementation along with an unstructured Euler solver where aerodynamic sensitivities are provided by discrete adjoint. The optimisation results show consistent reductions in both wave drag and induced drag while satisfying the aerodynamic constraints thereby demonstrating the effectiveness afforded by surface splines for shape optimisation.

关键词： Shape Control Aerodynamic Shape Optimization Shape Optimization sequential quadratic programming Wing Shape Optimization Wing Geometry Computer Aided Design Numerical Analysis Finite Volume Method Search Algorithm

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