查看更多>>摘要:With the development of information technology,a large number of product quality data in the entire manufacturing process is accumulated,but it is not explored and used effec-tively.The traditional product quality prediction models have many disadvantages,such as high complexity and low accuracy.To overcome the above problems,we propose an optimized data equalization method to pre-process dataset and design a simple but effective product quality prediction model:radial basis function model optimized by the firefly algorithm with Levy flight mechanism(RBFFALM).First,the new data equalization method is introduced to pre-process the dataset,which reduces the dimension of the data,removes redundant features,and improves the data distribution.Then the RBFFALFM is used to predict product quality.Comprehensive expeūriments conducted on real-world product quality datasets validate that the new model RBFFALFM combining with the new data pre-processing method outperforms other previous meūthods on predicting pro-duct quality.
查看更多>>摘要:Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popu-lar,since it can help to improve customer satisfaction,and ulti-mately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance ser-vice contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are con-ducted.The results show that by taking into account the incen-tive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.
查看更多>>摘要:Dominant technology formation is the key for the high-tech industry to"cross the chasm"and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the domi-nant technology by exploring its formation process and mecha-nism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is"stimulus-reaction-selection",which promotes the dominant technology's formation.(ii)The domi-nant technology's formation can be described as a dynamic pro-cess in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology's formation in the high-tech indus-try is influenced by learning ability,the number of adopting users and adaptability.Therein,a"critical scale"of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology's formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology's formation.(iv)The socio-technical landscape can promote the leading technology's shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.
查看更多>>摘要:At present,although knowledge graphs have been widely used in various fields such as recommendation systems,question and answer systems,and intelligent search,there are always quality problems such as knowledge omissions and errors.Quality assessment and control,as an important means to ensure the quality of knowledge,can make the applications based on knowledge graphs more complete and more accurate by reasonably assessing the knowledge graphs and fixing and improving the quality problems at the same time.Therefore,as an indispensable part of the knowledge graph construction pro-cess,the results of quality assessment and control determine the usefulness of the knowledge graph.Among them,the assessment and enhancement of completeness,as an impor-tant part of the assessment and control phase,determine whether the knowledge graph can fully reflect objective pheno-mena and reveal potential connections among entities.In this paper,we review specific techniques of completeness assess-ment and classify completeness assessment techniques in terms of closed world assumptions,open world assumptions,and par-tial completeness assumptions.The purpose of this paper is to further promote the development of knowledge graph quality control and to lay the foundation for subsequent research on the completeness assessment of knowledge graphs by reviewing and classifying completeness assessment techniques.
查看更多>>摘要:The rapid growth of mobile applications,the popula-rity of the Android system and its openness have attracted many hackers and even criminals,who are creating lots of Android malware.However,the current methods of Android malware detection need a lot of time in the feature engineering phase.Furthermore,these models have the defects of low detection rate,high complexity,and poor practicability,etc.We analyze the Android malware samples,and the distribution of malware and benign software in application programming interface(API)calls,permissions,and other attributes.We classify the software's threat levels based on the correlation of features.Then,we pro-pose deep neural networks and convolutional neural networks with ensemble learning(DCEL),a new classifier fusion model for Android malware detection.First,DCEL preprocesses the mal-ware data to remove redundant data,and converts the one-dimensional data into a two-dimensional gray image.Then,the ensemble learning approach is used to combine the deep neural network with the convolutional neural network,and the final clas-sification results are obtained by voting on the prediction of each single classifier.Experiments based on the Drebin and Malgenome datasets show that compared with current state-of-art models,the proposed DCEL has a higher detection rate,higher recall rate,and lower computational cost.
查看更多>>摘要:Aiming at the triangular fuzzy(TF)multi-attribute deci-sion making(MADM)problem with a preference for the distribu-tion density of attribute(DDA),a decision making method with TF number two-dimensional density(TFTD)operator is pro-posed based on the density operator theory for the decision maker(DM).Firstly,a simple TF vector clustering method is pro-posed,which considers the feature of TF number and the geo-metric distance of vectors.Secondly,the least deviation sum of squares method is used in the program model to obtain the den-sity weight vector.Then,two TFTD operators are defined,and the MADM method based on the TFTD operator is proposed.Finally,a numerical example is given to illustrate the superiority of this method,which can not only solve the TF MADM problem with a preference for the DDA but also help the DM make an overall comparison.
查看更多>>摘要:With the increasing precision of guidance,the impact of autopilot dynamic characteristics and target maneuvering abilities on precision guidance is becoming more and more sig-nificant.In order to reduce or even eliminate the autopilot dynamic operation and the target maneuvering influence,this paper suggests a guidance system model involving a novel inte-gral sliding mode guidance law(ISMGL).The method utilizes the dynamic characteristics and the impact angle,combined with a sliding mode surface scheme that includes the desired line-of-sight angle,line-of-sight angular rate,and second-order differen-tial of the angular line-of-sight.At the same time,the evaluation scenario considere the target maneuvering in the system as the external disturbance,and the non-homogeneous disturbance observer estimate the target maneuvering as a compensation of the guidance command.The proposed system's stability is proven based on the Lyapunov stability criterion.The simulations reveale that ISMGL effectively intercepted large maneuvering targets and present a smaller miss-distance compared with tra-ditional linear sliding mode guidance laws and trajectory shap-ing guidance laws.Furthermore,ISMGL has a more accurate impact angle and fast convergence speed.
查看更多>>摘要:The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance preci-sion.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-than-before impact on the main-body design(shape,motor,and lay-out design)and its design objective,i.e.,flight performance.Pur-suing a trade-off between flight performance and guidance pre-cision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,lay-out,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the gui-dance error.The problem is solved by using the nondominated sorting genetic algorithm Ⅱ.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.
查看更多>>摘要:In order to effectively defend against the threats of the hypersonic gliding vehicles(HGVs),HGVs should be tracked as early as possible,which is beyond the capability of the ground-based radars.Being benefited by the developing mega-constellations in low-Earth orbit,this paper proposes a relay tracking mode to track HGVs to overcome the above problem.The whole tracking mission is composed of several tracking intervals with the same duration.Within each tracking interval,several appropriate satellites are dispatched to track the HGV.Satellites that are planned to take part in the tracking mission are selected by a new derived observability criterion.The tracking performances of the proposed tracking mode and the other two traditional tracking modes,including the stare and track-rate modes,are compared by simulation.The results show that the relay tracking mode can track the whole trajectory of a HGV,while the stare mode can only provide a very short tracking arc.Moreover,the relay tracking mode achieve higher tracking accu-racy with fewer attitude controls than the track-rate mode.
查看更多>>摘要:The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the colli-sion detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-inter-est and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assign-ment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization inter-ests can effectively complete the task formation.