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Construction site accident analysis using text mining and natural language processing techniques

AUTOMATION IN CONSTRUCTION 2019年 99卷 238-248页

作者： Zhang, Fan Fleyeh, Hasan Wang, Xinru Lu, Minghui Dalarna Univ Dept Comp Engn S-79188 Falun Sweden Univ Nottingham Ningbo Res Ctr Fluids & Thermal Engn Ningbo 315100 Zhejiang Peoples R China Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200030 Peoples R China

Workplace safety is a major concern in many countries. Among various industries, construction sector is identified as the most hazardous work place. Construction accidents not only cause human sufferings but also result in huge financial loss. To prevent reoccurrence of similar accidents in the future and make scientific risk control plans, analysis of accidents is essential. In construction industry, fatality and catastrophe investigation summary reports are available for the past accidents. In this study, text mining and natural language process (NLP) techniques are applied to analyze the construction accident reports. To be more specific, five baseline models, support vector machine (SVM), linear regression (LR), K-nearest neighbor (KNN), decision tree (DT), Naive Bayes (NB) and an ensemble model are proposed to classify the causes of the accidents. Besides, sequential quadratic programming (SQP) algorithm is utilized to optimize weight of each classifier involved in the ensemble model. Experiment results show that the optimized ensemble model outperforms rest models considered in this study in terms of average weighted F1 score. The result also shows that the proposed approach is more robust to cases of low support. Moreover, an unsupervised chunking approach is proposed to extract common objects which cause the accidents based on grammar rules identified in the reports. As harmful objects are one of the major factors leading to construction accidents, identifying such objects is extremely helpful to mitigate potential risks. Certain limitations of the proposed methods are discussed and suggestions and future improvements are provided.

关键词： Construction site accident analysis Machine learning Text mining Natural language processing sequential quadratic programming Optimization

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A novel data-driven controller for plug-in hybrid electric vehicles with improved adaptabilities to driving environment

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JOURNAL OF CLEANER PRODUCTION 2022年 334卷

作者： Liu, Yu Zhang, Yuanjian Yu, Hanzhengnan Nie, Zhigen Liu, Yonggang Chen, Zheng China Automot Technol & Res Ctr Co Ltd Tianjin 300300 Peoples R China Loughborough Univ Dept Aeronaut & Automot Engn Loughborough LE11 3TU Leics England Kunming Univ Sci & Technol Fac Transportat Engn Kunming 650500 Yunnan Peoples R China Chongqing Univ State Key Lab Mech Transmiss Chongqing 400044 Peoples R China Chongqing Univ Sch Automot Engn Chongqing 400044 Peoples R China

Instantaneous application optimality is one of the indispensable indicators to assess energy management performance of plug-in hybrid electric vehicles (PHEVs). The momentary optimality, nevertheless, cannot be flexibly reachable under various driving environments due to the partial unobservabilities in control algorithms. To cope with it, a novel data-driven controller for PHEVs is proposed in this paper to achieve the instantaneous optimality of energy management. The well-designed machine learning based controller translates the knowledge of global optimization to real-time controlling scheme with the consideration of adaptabilities to disperse driving conditions. To start with, the universal global optimal control policies for varying driving environment are generated offline based on the chaotic quantum particle swarm optimization with sequential quadratic programming (CQPSO-SQP). Then, the offline optimized global control policies are assembled to construct the dataset for training the least square support vector machine (LSSVM) based controller, which features the superior capability in instantly optimal policy making under different driving conditions. At last, the detailed assessment is performed in simulation test and hardware-in-loop (HIL) test to validate the promising role of CQPSO-PSO and LSSVM in designing the novel energy management controller, and the corresponding results highlight the preferable controlling performance of the proposed novel controller in practical applications.

关键词： Plug-in hybrid electric vehicles Quantum particle swarm optimization Chaotic optimization sequential quadratic programming Least square support vector machine

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Superlinear convergence of a stabilized SQP method to a degenerate solution

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 1998年第3期11卷 253-275页

作者： Wright, SJ Argonne Natl Lab Div Math & Comp Sci Argonne IL 60439 USA

We describe a slight modification of the well-known sequential quadratic programming method for nonlinear programming that attains superlinear convergence to a primal-dual solution even when the Jacobian of the active constraints is rank deficient at the solution. We show that rapid convergence occurs even in the presence of the roundoff errors that are introduced when the algorithm is implemented in floating-point arithmetic.

关键词： nonlinear programming sequential quadratic programming degenerate solutions

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Optimization of Impulsive Trajectories from Circular Orbit to an Excess Velocity Vector

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第1期35卷 234-244页

作者： Jones, D. R. Ocampo, C. Univ Texas Austin Dept Aerosp Engn & Engn Mech WR Woolrich Labs Austin TX 78712 USA

Feasible transfer trajectories are constructed to serve as initial guesses for determining constrained optimal impulsive escape trajectories, from a circular orbit to a target hyperbolic excess velocity vector. The proximity of these feasible solutions to their corresponding optima are quantified. The objective of this work is to improve the feasible solutions, thereby enabling general anytime escape trajectories to be targeted that result in substantially reduced fuel expenditure. The procedure is currently restricted to one- and three-impulse escape trajectories from a circular parking orbit. Two separate three-impulse methods are presented, each specific to whether the time of flight is free or fixed. Numerical results, obtained using nonlinear programming algorithms, are presented to validate the robustness of the method. Analysis and results are nondimensional, and therefore are applicable to departures from a circular orbit about any celestial body.

关键词： Trans Earth Injection Parking Orbit Nonlinear programming Periapsis sequential quadratic programming Kepler's Equation Earth Trajectory Optimization Numerical Integration Space Exploration

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A hybrid FCASO-SQP method for solving the economic dispatch problems with valve-point effects

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ENERGY 2012年第1期38卷 346-353页

作者： Cai, Jiejin Li, Qiong Li, Lixiang Peng, Haipeng Yang, Yixian Sun Yat Sen Univ Sch Phys & Engn Guangzhou 510275 Guangdong Peoples R China Sun Yat Sen Univ Sino French Inst Nucl Engn & Technol Guangzhou 510275 Guangdong Peoples R China S China Univ Technol State Key Lab Subtrop Bldg Sci Guangzhou 510640 Guangdong Peoples R China Beijing Univ Posts & Telecommun Informat Secur Ctr Beijing 100876 Peoples R China

In this paper, a hybrid method integrating the fuzzy adaptive chaotic ant swarm optimization (FCASO) algorithm and the sequential quadratic programming (SQP) techniques, named FCASO-SQP method, is presented for solving the economic dispatch (ED) problems in power systems. The FCASO algorithm is the main optimizer in the hybrid method and the SQP technique is used to fine tune its results to improve the solution. The FCASO algorithm introduces a fuzzy system to dynamically tune the characteristic parameters psi(d) and r(i) of chaotic ant swarm optimization (CASO). The proposed method was applied to three different cases of power systems with three units, thirteen units and forty units, and the simulation results demonstrate its applicability and effectiveness to solve the ED problems with valve-point effect. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Economic dispatch Fuzzy adaptive chaotic ant swarm optimization sequential quadratic programming Evolutionary algorithm Power system

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Combining the regularization strategy and the SQP to solve MPCC - A MATLAB implementation

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2011年第18期235卷 5348-5356页

作者： Monteiro, M. Teresa T. Rodrigues, Helena Sofia Univ Minho Dept Prod & Sistemas P-4710057 Braga Portugal Inst Politecn Viana Castelo Escola Super Ciencias Empresariais P-4930678 Valenca Portugal

Mathematical Program with Complementarity Constraints (MPCC) plays a very important role in many fields such as engineering design, economic equilibrium, multilevel games, and mathematical programming theory itself. In theory its constraints fail to satisfy a standard constraint qualification such as the linear independence constraint qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ) at any feasible point. As a result, the developed nonlinear programming theory may not be applied to MPCC class directly. Nowadays, a natural and popular approach is trying to find some suitable approximations of an MPCC so that it can be solved by solving a sequence of nonlinear programs. This work aims to solve the MPCC using nonlinear programming techniques, namely the SQP and the regularization scheme. Some algorithms with two iterative processes, the inner and the external, were developed. A set of AMPL problems from MacMPEC database (Leyffer, 2000) [8] were tested. The comparative analysis regarding performance of algorithms was carried out. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Mathematical program with complementarity constraints sequential quadratic programming Nonlinear programming Regularization scheme

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A hybrid optimisation method for intercepting satellite trajectory based on differential game

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AERONAUTICAL JOURNAL 2023年第1312期127卷 900-922页

作者： Wu, W. Chen, J. Liu, J. Northwestern Polytech Univ ShaanXi Aerosp Flight Vehicle Design Key Lab Xian 710072 Shaanxi Peoples R China Beijing Inst Astronaut Syst Engn Beijing 100076 Peoples R China Sci & Technol Space Phys Lab Beijing 100076 Peoples R China

This study addresses orbit design and optimisation for the situation of satellite interception in which the target spacecraft is capable of manoeuvring using continuous magnitude restricted thrust. For the purpose of designing a long-range continuous thrust interception orbit, the orbit motion equations of two satellites with J2 perturbation are constructed. This problem is assumed to be a typical pursuit-evasion problem in differential game theory;using boundary constraint conditions and a performance index function that includes time and fuel consumption, the saddle point solution corresponding to the bilateral optimal is derived, and then this pursuit-evasion problem is transformed into a two-point boundary value problem. A hybrid optimisation method using a genetic algorithm (GA) and sequential quadratic programming (SQP) is derived to obtain the optimal control strategy. The proposed model and algorithm are proved to be feasible for the given simulation cases.

关键词： Satellite interception Differential game Genetic algorithm sequential quadratic programming Orbit design and optimisation

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Computational Design of Microvascular Radiative Cooling Panels for Nanosatellites

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JOURNAL OF THERMOPHYSICS AND HEAT TRANSFER 2018年第3期32卷 605-616页

作者： Tan, Marcus Hwai Yik Bunce, Devin Ghosh, Alexander R. M. Geubelle, Philippe H. Univ Illinois Dept Mech Sci & Engn Urbana IL 61801 USA Univ Illinois Dept Aerosp Engn 306F Talbot Lab104 South Wright St Urbana IL 61801 USA

This novel application of microvascular panels as nanosatellite radiator panels involves the key challenge of satisfying design constraints involving the coolant temperatures and pressure drop across the microchannel network. To address this challenge, the radiator panels are represented by dimensionally reduced hydraulic and nonlinear thermal models. The interface-enriched generalized finite element method and the Newton-Raphson scheme are then combined to solve the resulting nonlinear equations. Next, an interface-enriched generalized finite element method-based sensitivity analysis of the nonlinear equations is developed and combined with an existing sequential quadratic programming algorithm to solve an optimization problem specifically formulated to optimize the thermal performance of the radiator. The resulting thermal performance of the optimized designs is not only superior to that of the reference designs but is also in excellent agreement with an analytical model derived based on the assumption of near-monotonic variation in the coolant temperature along the microchannel network. A feasibility study on a reference design and an optimized design shows that only the latter can satisfy all design constraints with appropriately chosen flow rates. Solutions of the thermal and hydraulic models are also verified with ANSYS FLUENT simulations.

关键词： Coolant Nanosatellite Generalized Finite Element Method Radiator Panel Dirac Delta Function ANSYS FLUENT Thermal Performance sequential quadratic programming Radiative Cooling Thermal Modeling

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Parallel computing in water network analysis and leakage minimization

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT-ASCE 2000年第4期126卷 251-260页

作者： Alonso, JM Alvarruiz, F Guerrero, D Hernández, V Ruiz, PA Vidal, AM Martínez, F Vercher, J Ulanicki, B Univ Politecn Valencia Dept Sistemas Informat & Computac Parallel Comp Grp Valencia 46022 Spain Univ Politecn Valencia Dept Ingn Hidraul & Med Ambiente Valencia 46022 Spain De Montfort Univ Leicester LE1 9BH Leics England

In this paper a parallel computing based software demonstrator for the simulation and leakage minimization of water networks is presented. This demonstrator, based on the EPANET package, tackles three different types of problems making use of parallel computing. First, the solution of the hydraulic problem is treated by means of the gradient method. The key point in the parallelization of the method is the solution of the underlying linear systems, which is carried out by means of a multifrontal Choleski method. Second, the water quality simulation problem is approached by using the discrete volume element method. The application of parallel computing is based on dividing the water network in several parts using the multilevel recursive bisection graph partitioning algorithm. Finally, the problem of leakage minimization using pressure reducing valves is approached. This results in the formulation of an optimization problem for each time step, which is solved by means of sequential quadratic programming. Because these subproblems are independent of each other, they can be solved in parallel.

关键词： sequential quadratic programming pressure reducing valves PARALLEL PROCESSING (COMPUTERS) parallelization Network analysis

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Application of SQP and dynamic mode tracking to the determination of the critical speed of rail vehicles

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INTERNATIONAL JOURNAL OF HEAVY VEHICLE SYSTEMS 2007年第2期14卷 193-212页

作者： He, Yuping McPhee, John Univ Ontario Inst Technol Fac Engn & Appl Sci Oshawa ON L1H 7K4 Canada Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada

A method is presented for determining the critical speed of rail vehicles. Dynamic Mode Tracking (DMT) is used to identify the dynamic modes for a given speed and a sequential quadratic programming (SQP) algorithm determines the critical speed at which the least-damped mode has zero damping. It is shown that the SQP algorithm without DMT often fails to find the critical speed. In comparison, the combined SQP-DMT algorithm provides a reliable identification of the critical speed. This integrated algorithm can be applied to rotor dynamics, wind turbine dynamics, aeronautics, and road vehicle dynamics for automatically identifying the critical speed corresponding to a linear stability analysis.

关键词： sequential quadratic programming SQP dynamic mode tracking DMT critical speed identification rail vehicles

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