Optimizing a Transportation System Using Metaheuristics Approaches (EGD/GA/ACO): A Forest Vehicle Routing Case Study

The large-scale optimization problem requires some optimization techniques, and the Metaheuristics approach is highly useful for solving difficult optimization problems in practice. The purpose of the research is to optimize the transportation system with the help of this approach. We selected forest vehicle routing data as the case study to minimize the total cost and the distance of the forest transportation system. Matlab software helps us find the best solution for this case by applying three algorithms of Metaheuristics: Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Extended Great Deluge (EGD). The results show that GA, compared to ACO and EGD, provides the best solution for the cost and the length of our case study. EGD is the second preferred approach, and ACO offers the last solution.

Organic cathode materials for rechargeable magnesium-ion batteries:Fundamentals, recent advances, and approaches to optimization

Rechargeable magnesium-ion batteries(MIBs) are favorable substitutes for conventional lithium-ion batteries(LIBs) because of abundant magnesium reserves, a high theoretical energy density, and great inherent safety. Organic electrode materials with excellent structural tunability,unique coordination reaction mechanisms, and environmental friendliness offer great potential to promote the electrochemical performance of MIBs. However, research on organic magnesium battery cathode materials is still preliminary with many significant challenges to be resolved including low electrical conductivity and unwanted but severe dissolution in useful electrolytes. Herein, we provide a detailed overview of reported organic cathode materials for MIBs. We begin with basic properties such as charge storage mechanisms(e.g., n-, p-, and bipolartype), moving to recent advances in various types of organic cathodes including carbonyl-, nitrogen-, and sulfur-based materials. To shed light on the diverse strategies targeting high-performance Mg-organic batteries, elaborate summaries of various approaches are presented.Generally, these strategies include molecular design, polymerization, mixing with carbon, nanosizing and electrolyte/separator optimization.This review provides insights on exploring high-performance organic cathodes in rechargeable MIBs.

Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

Optimal Design of Equivalent Water Depth Truncated Mooring System Based on Baton Pattern Simulated Annealing Algorithm

The highest similarity degree of static characteristics including both horizontal and vertical restoring force-displacement characteristics of total mooring system, as well as the tension-displacement characteristics of the representative single mooring line between the truncated and full depth system are obtained by annealing simulation algorithm for hybrid discrete variables （ASFHDV, in short）. A“baton” optimization approach is proposed by utilizing ASFHDV. After each baton of optimization, if a few dimensional variables reach the upper or lower limit, the boundary of certain dimensional variables shall be expanded. In consideration of the experimental requirements, the length of the upper mooring line should not be smaller than 8 m, and the diameter of the anchor chain on the bottom should be larger than 0.03 m. A 100000 t turret mooring FPSO in the water depth of 304 m, with the truncated water depth being 76 m, is taken as an example of equivalent water depth truncated mooring system optimal design and calculation, and is performed to obtain the conformation parameters of the truncated mooring system. The numerical results indicate that the present truncated mooring system design is successful and effective.

Review of JONSWAP Spectrum Based on Storm 149 from North Alwyn

The measured spectrum for Storm 149 from North Alwyn is calculated by use of FFT (Fast Fourier Transformation) arithmetic and its statistical characteristics are used to determine the predicted spectrum in which the JONSWAP formula is adopted to review comparative object. It is shown that the agreement between measured and predicted spectrum is satisfactory and some corrections to the parameters for the JONSWAP formula are necessary.

Fault detection and optimization for networked control systems with uncertain time-varying delay

The observer-based robust fault detection filter design and optimization for networked control systems （NOSs） with uncer- tain time-varying delays are addressed. The NCSs with uncertain time-varying delays are modeled as parameter-uncertain systems by the matrix theory. Based on the model, an observer-based residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of the linear matrix inequality. Furthermore, a time domain opti- mization approach is proposed to improve the performance of the fault detection system. To prevent the false alarms, a new thresh- old function is established, and the solution of the optimization problem is given by using the singular value decomposition （SVD） of the matrix. A numerical example is provided to illustrate the effectiveness of the proposed approach.

Signal processing method for shear wave velocity measurement

Soil shear wave velocity （SWV） is an important parameter in geotechnical engineering. To measure the soil SWV, three methods are generally used in China, including the single-hole method, cross-hole method and the surface-wave technique. An optimized approach based on a correlation function for single-hole SWV measurement is presented in this paper. In this approach, inherent inconsistencies of the artificial methods such as negative velocities, and too-large and too-small velocities, are eliminated from the single-hole method, and the efficiency of data processing is improved. In addition, verification using the cross-hole method of upper measuring points shows that the proposed optimized approach yields high precision in signal processing.

Optimal paths planning in dynamic transportation networks with random link travel times

A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.

On Advanced Control Methods toward Power Capture and Load Mitigation in Wind Turbines

This article provides a survey of recently emerged methods for wind turbine control. Multivariate control approaches to the optimization of power capture and the reduction of loads in components under time-varying turbulent wind fields have been under extensive investigation in recent years. We divide the related research activities into three categories： modeling and dynamics of wind turbines, active control of wind turbines, and passive control of wind turbines. Regarding turbine dynamics, we discuss the physical fundamentals and present the aeroelastic analysis tools. Regarding active control, we review pitch control, torque control, and yaw control strategies encompassing mathematical formulations as well as their applications toward different objectives. Our survey mostly focuses on blade pitch control, which is considered one of the key elements in facilitating load reduction while maintaining power capture performance. Regarding passive control, we review techniques such as tuned mass dampers, smart rotors, and microtabs. Possible future directions are suggested.

ON APPROXIMATE EFFICIENCY FOR NONSMOOTH ROBUST VECTOR OPTIMIZATION PROBLEMS

In this article,we use the robust optimization approach(also called the worst-case approach)for findingε-efficient solutions of the robust multiobjective optimization problem defined as a robust(worst-case)counterpart for the considered nonsmooth multiobjective programming problem with the uncertainty in both the objective and constraint functions.Namely,we establish both necessary and sufficient optimality conditions for a feasible solution to be anε-efficient solution(an approximate efficient solution)of the considered robust multiobjective optimization problem.We also use a scalarizing method in proving these optimality conditions.

Extraction of optical constants and thickness of nanometre scale TiO2 film

TiO2 thin films were deposited on glass substrates by sputtering in a conventional rf magnetron sputtering system. X-ray diffraction pattern and transmission spectrum were measured. The curves of refraction index and extinction coefficient distributions as well as the thickness of films calculated from transmission spectrum were obtained. The optimization problem was also solved using a method based on a constrained nonlinear programming algorithm.

The Optimized Way of Commercial Bank Management under the Background of Big Data

With the advent of the era of big data,the commercial management activities of commercial banks are facing both new challenges and new development opportunities.In the increasingly fierce market competition,commercial banks must pay attention to enhance their core competitiveness,only in this way can they occupy a certain advantage in the fierce market environment.Therefore,commercial banks must accurately grasp the development opportunities brought by big data,and further strengthen the optimization of business management.The author explores and analyzes the impact of big data on commercial banks,and puts forward an effective way for commercial banks to optimize business management in the context of big data,hoping to contribute to the long-term development of commercial banks.

Robust parametric approach for tracking control of an air-breathing hypersonic cruise vehicle

To realize the stabilization and the tracking of flight control for an air-breathing hypersonic cruise vehicle, the linearization of the longitudinal model under trimmed cruise condition is processed firstly. Furthermore, the flight control problem is formulated as a robust model tracking control problem. And then, based on the robust parametric approach, eigenstructure assignment and reference model tracking theory, a parametric optimization method for robust controller design is presented. The simulation results show the effectiveness of the proposed approach.

Experimental validation of double-fed induction generator in oscillating water column using circulatory system-based optimization

This paper validates the optimal operation for a grid-connected double-fed induction generator(DFIG)in an oscillating water column power plant(OWCPP).This study presents a novel optimization technique called the circulatory system-based optimization(CSBO)approach to develop six adaptive fuzzy logic controllers(AFLCs)with 30 parameters and compare them to chaotic-billiards optimization(C-BO)and genetic algorithm(GA).The proposed controller is also compared with a proportional-integral differential(PID)controller based on a self-adaptive global-best harmony search(SGHS).CSBO-based AFLCs are fully investigated under different scenarios and experimented with using a real-time interface DSP1104.The results of using CSBO-AFLCs revealed a fast time response,fast convergence,less overshoot and minimal error compared with those achieved with C-BO-AFLC,SGHS-PID and GA-AFLC during different case studies.The CSBO-based AFLCs ensure maximum power from the DFIG in an OWCPP and enhance dynamic response with very low errors.The results show that the CSBO shows better power tracking by 25%as compared with C-BO,by 45%when compared with the GA and by 56%when compared with PID.Moreover,the integral absolute errors of six controllers are investigated to demonstrate the feasibility of CSBO-AFLC.The root mean square of the errors of six controllers using CSBO is improved by 68.27%when compared with GA,by 22.57%when compared with C-BO and by 38.42%when compared with PID.These indicators demonstrate the feasibility of CSBO when compared with other algorithms with the same OWCPP.

Communication security of autonomous ground vehicles based on networked control systems:The optimized LMI approach

The paper presents a study of networked control systems(NCSs)that are subjected to periodic denial-of-service(DoS)attacks of varying intensity.The use of appropriate Lyapunov-Krasovskii functionals(LKFs)help to reduce the constraints of the basic conditions and lower the conservatism of the criteria.An optimization problem with constraints is formulated to select the trigger threshold,which is solved using the gradient descent algorithm(GDA)to improve resource utilization.An intelligent secure event-triggered controller(ISETC)is designed to ensure the safe operation of the system under DoS attacks.The approach is validated through experiments with an autonomous ground vehicle(AGV)system based on the Simulink platform.The proposed method offers the potential for developing effective defense mechanisms against DoS attacks in NCSs.

An improved equivalent beam model of large periodic beam-like space truss structures

Space truss structures are essential components for space-based remote sensing loads with high spatial and temporal resolutions.To achieve high-precision vibration control,an accurate and efficient dynamics model is essential.In addition to the current equivalent beam model(EBM)based on the classical continuum theory,an improved equivalent beam model(IEBM)is proposed that considers the impact of the distinction between trusses and beams on torsional and shear deformations,as well as the impact of shear deformation on flexural rigidity.According to the displacement expressions of spatial beams,torsional,shear,and bending correction coefficients are introduced to derive expressions of strain energy and kinetic energy.The energy equivalence principle is then utilized to calculate the elasticity and inertia matrices,and dynamics equations are established using the finite element method.Subsequently,an IEBM is constructed by employing the particle swarm optimization approach to determine the correction coefficients with the truss natural frequency as the optimization target.The natural vibration characteristics of the structure are estimated for various material properties.Compared with the full-scale finite element model,the EBM reaches a maximum error of 80%for a low modulus of elasticity,while the maximum error of the IEBM is less than 2%for any given parameters,indicating its superior accuracy to the EBM.

A Gradient-Based Optimization Method for the Design of Layered Phononic Band-Gap Materials

Phononic materials with specific band-gap characteristics at desired frequency ranges are in great demand for vibration and noise isolation, elastic wave filters, and acoustic devices. The attenuation coefficient curve depicts both the frequency range of band gap and the attenuation of elastic wave, where the frequency ranges corresponding to the none-zero attenuation coefficients are band gaps. Therefore, the band-gap characteristics can be achieved through maximizing the attenuation coefficient at the corresponding frequency or within the corresponding frequency range. Because the attenuation coefficient curve is not smooth in the frequency domain, the gradient-based optimization methods cannot be directly used in the design optimization of phononic band-gap materials to achieve the maximum attenuation within the desired frequency range. To overcome this difficulty, the objective of maximizing the attenuation coefficient is transformed into maximizing its Cosine, and in this way, the objective function is smoothed and becomes differentiable. Based on this objective function, a novel gradient-based optimization approach is proposed to open the band gap at a prescribed frequency range and to further maximize the attenuation efficiency of the elastic wave at a specific frequency or within a prescribed frequency range. Numerical results demonstrate the effectiveness of the proposed gradient-based optimization method for enhancing the wave attenuation properties.

Estimation of hydraulic parameters from pumping tests in a multiaquifer system

The hydrogeologic conditions in Tianjin,China,are characterized by a system of multiple alternating aquifers and aquitards and a high groundwater level.Generally,the groundwater system to a depth of 70 m includes one phreatic aquifer and three semiconfined aquifers(AqI–AqIII).The distribution of aquifers varies greatly.Accurate estimates of aquifer parameters from pumping tests are essential in geotechnical engineering practice.In this study,the applicability of different models for estimating hydraulic parameters in a multiaquifer system is analyzed.To avoid errors in the graphic-analytical process and to enhance the efficiency and accuracy,a hybrid algorithm,called GALMA(a genetic algorithm(GA)combined with the Levenberg–Marquardt(LM)algorithm),is used with the Neuman and Witherspoon model and ratio method.The estimated values in the second and third semiconfined aquifers(AqII and AqIII)from various solutions are compared with the measured data.Further validations based on the prediction of the drawdown values are performed via a three dimensional numerical simulation.

Structural-acoustic topology optimization analysis based on evolutionary structural optimization approach

The continuum structural-acoustic topology optimization with external loading is investigated herein. Finite element method （FEM） is used to obtain the structural frequency response and boundary element method （BEM） is adopted to perform exterior acoustic radiation analysis. The evolutionary structural optimization （ESO） is served as an optimization method in structural-acoustic radiation topology analysis. The acoustic radiation optimization of a plate under harmonic excitation is given for example. The numerical results show that using ESO solution to analyze structural-acoustic topology optimization is feasible and effective.

Scheme-scale ambiguity in analysis of QCD observable

The scheme-scale ambiguity that has plagued perturbative analysis in QCD remains on obstacle to making precise tests of the theory.Many attempts have been done to resolve the scale ambiguity.In this regard the BLM,EC,PMS and CORGI approaches are more distinct.We try to employ these methods to fix the scale ambiguity at NLO,NNLO and even in more higher order approximations.By optimizing the renormalization scale,there will be a possibility to predicate higher order terms.We present general results for predicted terms at any order,using different optimization methods.Some observable as specific examples will be used to indicate the validity of scale fixing to predicate the higher order terms.