Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization

In multimodal multiobjective optimization problems(MMOPs),there are several Pareto optimal solutions corre-sponding to the identical objective vector.This paper proposes a new differential evolution algorithm to solve MMOPs with higher-dimensional decision variables.Due to the increase in the dimensions of decision variables in real-world MMOPs,it is diffi-cult for current multimodal multiobjective optimization evolu-tionary algorithms(MMOEAs)to find multiple Pareto optimal solutions.The proposed algorithm adopts a dual-population framework and an improved environmental selection method.It utilizes a convergence archive to help the first population improve the quality of solutions.The improved environmental selection method enables the other population to search the remaining decision space and reserve more Pareto optimal solutions through the information of the first population.The combination of these two strategies helps to effectively balance and enhance conver-gence and diversity performance.In addition,to study the per-formance of the proposed algorithm,a novel set of multimodal multiobjective optimization test functions with extensible decision variables is designed.The proposed MMOEA is certified to be effective through comparison with six state-of-the-art MMOEAs on the test functions.

Phase-Based Optical Flow Method with Optimized Parameter Settings for Enhancing Displacement Measurement Adaptability

To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizing parameter settings is proposed. The optimized parameters include the best measurement points of the Region of Interest (ROI) and the levels of pyramid filters. Additionally, to address the issue of updating reference frames in practical applications due to the difficulty in estimating the maximum effective measurement value, a mechanism for dynamically updating reference frames is introduced. Experimental results demonstrate that compared to representative image gradient-based displacement measurement methods, the proposed method exhibits higher measurement accuracy in engineering applications. This provides reliable data support for structural damage identification research based on vibration signals and is expected to broaden the engineering application prospects for structural health monitoring.

LOCATORS OPTIMIZATION FOR MEASURING FIXTURE DESIGN

'N-2-1' principle is widely recognized in the fixture design for deformablesheet metal workpieces, where N, the locators on primary datum, is the key to sheet metal fixturedesign. However, little research is done on how to determine the positions and the number of Nlocators. In practice, the N locators are frequently designed from experience, which is oftenunsatisfactory for achieving the precision requirement in fixture design. A new method to lay outthe N locators for measuring fixture of deformable sheet metal workpiece is presented, given thefixed number of A'. Finite-element method is used to model and analysis the deformation of differentlocator layouts. A knowledge based genetic algorithm (KBGA) is applied to identify the optimumlocator layout for measuring fixture design. An example of a door outer is used to verify theoptimization approach.

Flow measurement and parameter optimization of right-angled flow passage in hydraulic manifold block

This study was conducted to investigate the flow field characteristics of right-angled flow passage with various cavities in the typical hydraulic manifold block.A low-speed visualization test rig was developed and the flow field of the right-angled flow passage with different cavity structures was measured using 2D-PIV technique.Numerical model was established to simulate the three-dimensional flow field.Seven eddy viscosity turbulence models were investigated in predicting the flow field by comparing against the particle image relocimetry(PIV)measurement results.By defining the weight error function K,the S-A model was selected as the appropriate turbulence model.Then,a three-factor,three-level response surface numerical test was conducted to investigate the influence of flow passage connection type,cavity diameter and cavity length-diameter ratio on pressure loss.The results show that the Box-Benhnken Design(BBD)model can predict the total pressure loss accurately.The optimal factor level appeared in flow passage connection type II,14.64 mm diameter and 67.53%cavity length-diameter ratio.The total pressure loss decreased by 11.15%relative to the worst factor level,and total pressure loss can be reduced by 64.75%when using an arc transition right-angled flow passage,which indicates a new direction for the optimization design of flow passage in hydraulic manifold blocks.

Optimization model of unascertained measurement for underground mining method selection and its application

An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.

Perforation optimization of layer-penetration fracturing for commingling gas production in coal measure strata

Optimization of fracturing perforation is of great importance to the commingling gas production in coal measure strata.In this paper,a 3 D lattice algorithm hydraulic fracturing simulator was employed to study the effects of perforation position and length on hydraulic fracture propagation in coal measures of the Lin-Xing block,China.Based on field data,three lithologic combinations are simulated:1)a thick section of coal seam sandwiched by sandstones;2)a thin coal seam layer overlay by gas-bearing tight sandstone;3)two coal seams separated by a thin layer of sandstone.Our simulation shows that perforation position and length in multi-layer reservoirs play a major role in hydraulic fracture propagation.Achieving maximum stimulated volume requires consideration of lithologic sequence,coal seam thickness,stress states,and rock properties.To improve the combined gas production in coal measure strata,it is possible to simultaneously stimulate multiple coal seams or adjacent gas-bearing sandstones.In these cases,perforation location and length also significantly impact fracture propagation,and therefore should be carefully designed.Our simulation results using 3 D lattice algorithm are qualitatively consistent with laboratory physical simulation.3 D lattice models can be used to effectively simulate the fracture propagation through layers in coal measure strata.The numerical results provide guidance for perforation optimization in the hydraulic fracturing of coal measure strata.

A Spacecra Equipment Layout Optimization Method for Diverse and Competitive Design

The spacecraequipment layout optimization design(SELOD)problems with complicated performance con-straints and diversity are studied in this paper.The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases eectively.However,these local optimal solutions are too dicult to jump out of their current relative geometry relationships,signi􀀀cantly limiting their further improvement in performance indicators.Therefore,considering the geometric diversity of layout schemes is put forward to alleviate this limitation.First,similarity measures,including modi􀀀ed cosine similarity and gaussian kernel function similarity,are introduced into the layout optimization process.Then the optimization produces a set of feasible layout candidates with the most remarkable dierence in geometric distribution and the most representative schemes are sampled.Finally,these feasible geometric solutions are used as initial solutions to optimize the physical performance indicators of the spacecra,and diversi􀀀ed layout schemes of spacecraequipment are generated for the engineering practice.The validity and eectiveness of the proposed methodology are demonstrated by two SELOD applications.

An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

In uncertainty analysis and reliability-based multidisciplinary design and optimization(RBMDO)of engineering structures,the saddlepoint approximation(SA)method can be utilized to enhance the accuracy and efficiency of reliability evaluation.However,the random variables involved in SA should be easy to handle.Additionally,the corresponding saddlepoint equation should not be complicated.Both of them limit the application of SA for engineering problems.The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments.However,the traditional moment matching method is not very accurate generally.In order to take advantage of the SA method and the moment matching method to enhance the efficiency of design and optimization,a fourth-moment saddlepoint approximation(FMSA)method is introduced into RBMDO.In FMSA,the approximate cumulative generating functions are constructed based on the first four moments of the limit state function.The probability density function and cumulative distribution function are estimated based on this approximate cumulative generating function.Furthermore,the FMSA method is introduced and combined into RBMDO within the framework of sequence optimization and reliability assessment,which is based on the performance measure approach strategy.Two engineering examples are introduced to verify the effectiveness of proposed method.

Diurnal Variation of Soil CO2 Efflux and Its Optimal Measuring Time-window of Temperate Meadow Steppes in Western Songnen Plain, China

In order to study the diurnal variation of soil CO2 effiux from temperate meadow steppes in Northeast China, and determine the best time for observation, a field experiment was conducted with a LI-6400 soil CO2 flux system under five typical plant communi- ties （Suaeda glauca （Sg）, Chloris virgata （Cv）, Puecinellia distans （Pd）, Leymus chinensis （Lc） and Phragmites australis （Pa）） and an alkali-spot land （As） at the meadow steppe of western Songnen Plain. The results showed that the diurnal variation of soil CO2 effiux exhibited a single peak curve in the growing season. Diurnal maximum soil respiration （Rs） often appeared between 1 1：00 and 13：00, while the minimum occurred at 21：00-23：00 or before dawn. Air temperature near the soil surface （Ta） and soil temperature at 10 cm depth （Tlo） exerted dominant control on the diurnal variations of soil respiration. The time-windows 7：00-9：00 could be used as the optimal measuring time to represent the daily mean soil CO2 effiux at the Cv, Pd, Lc and Pa sites. The daily mean soil CO2 effiux was close to the soil COz effiux from 15：00 to 17：00 and the mean of 2 individual soil CO2 effiux from 15：00 to 19：00 at the As and Sg sites, respectively. During nocturnal hours, negative soil CO2 fluxes （CO2 downwards into the soil） were frequently observed at the As and Sg sites, the magnitude of the negative CO2 fluxes were 0.10-1.55 gmol/（m2.s） and 0.10-0.69 gmol/（m2.s）at the two sites. The results im- plied that alkaline soils could absorb CO2 under natural condition, which might have significant implications to the global carbon budget accounting.

Lifetime prediction for tantalum capacitors with multiple degradation measures and particle swarm optimization based grey model

A lifetime prediction method for high-reliability tantalum （Ta） capacitors was proposed, based on multiple degradation measures and grey model （GM）. For analyzing performance degradation data, a two-parameter model based on GM was developed. In order to improve the prediction accuracy of the two-parameter model, parameter selection based on particle swarm optimization （PSO） was used. Then, the new PSO-GM（1, 2, co） optimization model was constructed, which was validated experimentally by conducting an accelerated testing on the Ta capacitors. The experiments were conducted at three different stress levels of 85, 120, and 145℃. The results of two experiments were used in estimating the parameters. And the reliability of the Ta capacitors was estimated at the same stress conditions of the third experiment. The results indicate that the proposed method is valid and accurate.

COST 231-Hata Propagation Model Optimization in 1800 MHz Band Based on Magnetic Optimization Algorithm: Application to the City of Limbé

Network planning is essential for the construction and the development of wireless networks. The network planning cannot be possible without an appropriate propagation model which in fact is its foundation. Initially used mainly for mobile radio networks, the optimization of propagation model is becoming essential for efficient deployment of the network in different types of environment, namely rural, suburban and urban especially with the emergence of concepts such as digital terrestrial television, smart cities, Internet of Things (IoT) with wide deployment for different use cases such as smart grid, smart metering of electricity, gas and water. In this paper we use an optimization algorithm that is inspired by the principles of magnetic field theory namely Magnetic Optimization Algorithm (MOA) to tune COST231-Hata propagation model. The dataset used is the result of drive tests carry out on field in the town of Limbe in Cameroon. We take into account the standard K-factor model and then use the MOA algorithm in order to set up a propagation model adapted to the physical environment of a town. The town of Limbe is used as an implementation case, but the proposed method can be used everywhere. The calculation of the root mean square error (RMSE) between the real data from the radio measurements and the prediction data obtained after the implementation of MOA allows the validation of the results. A comparative study between the value of the RMSE obtained by the new model and those obtained by the optimization using linear regression, by the standard COST231-Hata models, and the free space model is also done, this allows us to conclude that the new model obtained using MOA for the city of Limbe is better and more representative of this local environment than the standard COST231-Hata model. The new model obtained can be used for radio planning in the city of Limbé in Cameroon.

Design on Improving Efficiency for Measuring System Integrated Test of A Space Vehicle

Measuring system is the core part of a space vehicle, and its integrated test is the important means of conducting system-level verification. For the integrated test items and flow, the solution featuring the automatic test method, the combination of different test items, and the electronic data record is proposed in this paper. Applying the above-mentioned solution, the test efficiency could be improved by more than 30% and the safety of test operation could be also exalted. At the same time, the solution has good universality and could provide reference for other similar integrated tests.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

A new method of phase measurement based on optimization

A new method of phase measurement based on optimization is presented. Simulations were ran with synthesized signals, and comparison was made with some spectral domain methods. The results show that, with a suitable number of samples processed, this method is superior to other methods in terms of accuracy, while the amplitude and phase of distortion component have no effect on accuracy.

Measures for the Optimization of Subgrade and Pavement Design in the Reconstruction and Expansion of Highways

In comparison to the construction of modern highway engineering,several of China’s early pavement construction concerns,such as pavement collapse,are rather clear.Limited by historical and technical factors,the subgrade and pavement design for highways lacks scientificity,thus inducing potential safety problems in the operation.In order to comprehensively improve the subgrade and pavement design as well as ensure the quality and safety of highway engineering projects,this paper takes the reconstructed and expanded highway projects as research subjects and focuses on proposing optimization measures for the subgrade and pavement design of reconstructed and expanded highways,so as to provide adequate reference.

Questions on Optimization of Measurement of Total Electron Content in Ionosphere with GPS

The analysis of existing method for calculation of total content of electrons (TEC) in ionosphere using GPS occultation method does show that due to different values of signal/noise ration in GPS signals ?and , the new method of optimum measurements of relevant frequency components of TEC measured by phase and code methods should be developed. The optimum quantity of measurements of the above-mentioned frequency components is determined taking into account the limitation imposed on general number of necessary measurements.

The Evolution of Landscape Patterns of and Optimization Measures for Urban Core Areas Against the Background of Urbanization: A Case Study of Yangling Demonstration Zone

Studying tiie urban landscape pattern plays a crucial role in scientific land use and management and in improving the urban ecological environment In this paper, AutoCAD, ArcGIS, Fragstats, and other software were used to analyse the data of the fourth phase of land use in the core atea of Yangling Demonstration Zone. The results showed that： ① in the core area, the percentage of construction land incteased from 18.22% to 61.72%, and the percentage of agricultufal land decreased from 58.36% to 11.14%. And the fafm land was fragmented, and traffic connectivily was strengthened. The afea of garden land was reduced from 251.89 hm2 to 50.38 hm^2, and the landscape metric of forest land showed an inverted V-shaped curve. ②The year 2009 in four phases witnessed the greatest landscape fragmentation, both Edge Density （ED） and Ingest Patch Index （LPI） increased, and human interference enhanced the overall landscape complexity. Measures were fotmulated in terms of deaf development goals, optimized allocation of land resoutces, effective protection of ecological ted lines, and definite ecological responsibility, so as to optimize the urban landscape pattern.

Numerical simulation and parameter optimization of Coriolis force scale measurement process based on DEM

The Coriolis force method is a recently developed and highly regarded direct measurement technique that enables high-precision measurement of bulk materials.The operational parameters and variations thereof directly influence the measurement accuracy of the equipment.In this study,a measurement correction coefficient is introduced to improve the calculation method for mass flow rate of the materials.The DEM is employed to simulate the motion of particle groups within the Coriolis force scale under different parameters,and the effects of various structural and operational parameters on the measurement results are compared.The research findings indicate that a lower rotational speed leads to more stable instantaneous measurement results,although the measurement error is relatively large.When the rotational speed exceeds 300 rpm,the measurement error remains within 15%.For materials with a radius of 1–2 mm,the variation range of precision error is approximately 0.4%.Among the structural parameters,the radius of the measurement wheel has the most significant impact on the measurement results,wherein a larger measurement wheel radius corresponds to a smaller measurement error.The horizontal angle of the blades follows as the next influential parameter,with a clockwise rotation and a horizontal angle of 30°resulting in a measurement error below 2%.

Optimization of the cavity beam-position monitor system for the Shanghai soft X-ray free-electron laser user facility

To achieve high-efficiency operation of the highgain free-electron laser(FEL),the electron beams and radiated photon beams need to be overlapped precisely and pass through the entire undulator section.Therefore,a high-resolution beam-position monitor(BPM)is required.A cavity BPM(CBPM)with a resonant cavity structure was developed and used in the Shanghai Soft X-ray FEL(SXFEL)test facility and can achieve a position resolution of<1μm.The construction and operation of the SXFEL user facility also bring about higher requirements for beamposition measurement.In this case,the factors that affect the performance of the CBPM system were further analyzed.These included the amplitude and phase stability of the local oscillator,stability of the trigger signal,performance of the radio frequency front-end,signal processing electronics,and signal processing algorithms.Based on the upgrade and optimization of the system,a beam test platform was built at the end of the linear acceleration section of the SXFEL,and the experimental results show that the position resolution of the system can reach 177 nm at a bunch charge of 500 pC,and the dynamic range is controlled within±300μm,and the relative measurement uncertainty of the bunch charge can reach 0.021%,which are significant improvements compared to the attributes of the previous system.

Decision Bayes Criteria for Optimal Classifier Based on Probabilistic Measures

This paper addresses the high dimension sample problem in discriminate analysis under nonparametric and supervised assumptions. Since there is a kind of equivalence between the probabilistic dependence measure and the Bayes classification error probability, we propose to use an iterative algorithm to optimize the dimension reduction for classification with a probabilistic approach to achieve the Bayes classifier. The estimated probabilities of different errors encountered along the different phases of the system are realized by the Kernel estimate which is adjusted in a means of the smoothing parameter. Experiment results suggest that the proposed approach performs well.