Dynamic plugging regulating strategy of pipeline robot based on reinforcement learning

Pipeline isolation plugging robot (PIPR) is an important tool in pipeline maintenance operation. During the plugging process, the violent vibration will occur by the flow field, which can cause serious damage to the pipeline and PIPR. In this paper, we propose a dynamic regulating strategy to reduce the plugging-induced vibration by regulating the spoiler angle and plugging velocity. Firstly, the dynamic plugging simulation and experiment are performed to study the flow field changes during dynamic plugging. And the pressure difference is proposed to evaluate the degree of flow field vibration. Secondly, the mathematical models of pressure difference with plugging states and spoiler angles are established based on the extreme learning machine (ELM) optimized by improved sparrow search algorithm (ISSA). Finally, a modified Q-learning algorithm based on simulated annealing is applied to determine the optimal strategy for the spoiler angle and plugging velocity in real time. The results show that the proposed method can reduce the plugging-induced vibration by 19.9% and 32.7% on average, compared with single-regulating methods. This study can effectively ensure the stability of the plugging process.

Dynamic Pricing Strategies Using Artificial Intelligence Algorithm

Pricing strategies can have a huge impact on a company’s success. This paper focuses on the advantages and disadvantages of using artificial intelligence in dynamic pricing strategies. A good understanding of the possible benefits and challenges will help companies to understand the impact of their chosen pricing strategies. AI-driven Dynamic pricing has great opportunities to increase a firm’s profits. Firms can benefit from personalized pricing based on personal behavior and characteristics, as well as cost reduction by increasing efficiency and reducing the need to use manual work and automation. However, AI-driven dynamic rewarding can have a negative impact on customers’ perception of trust, fairness and transparency. Since price discrimination is used, ethical issues such as privacy and equity may arise. Understanding the businesses and customers that determine pricing strategy is so important that one cannot exist without the other. It will provide a comprehensive overview of the main advantages and disadvantages of AI-assisted dynamic pricing strategy. The main objective of this research is to uncover the most notable advantages and disadvantages of implementing AI-enabled dynamic pricing strategies. Future research can extend the understanding of algorithmic pricing through case studies. In this way, new, practical implications can be developed in the future. It is important to investigate how issues related to customers’ trust and feelings of unfairness can be mitigated, for example by price framing.

Study on Dynamic Characteristics of Superconducting Electrodynamic Maglev Train

This study considers a superconducting electrodynamic maglev train of MLX01 type.The characteristics of the electromagnetic spring coefficient of a single bogie under different magnetomotive force(MF) of the superconducting coil and standard air gap(Sag) were explored.In view of the small electromagnetic damping,a passive damping control strategy and an active damping control strategy were designed to increase the electromagnetic damping force between the superconducting coil and ground coil.Combined with the coupling numerical model of a single bogie,the vibration characteristics of the bogie in different directions with different damping control strategies were studied when the Sag and MF were fixed.The results can provide important theoretical support for stable operation control of maglev trains.

Research on strategic risk identification method of equipment system development based on system dynamics

Strategic management of equipment system develop-ment must attach importance to effective strategic risk manage-ment.Aiming at the identification of strategic risk of equipment system development,firstly,the source of strategic risk of equip-ment system development is analyzed and classified.Based on this,a causal loop diagram of strategic risk of equipment sys-tem development based on system dynamics is established.The system dynamics analysis software Vensim PLE is used to carry out the risk influencing factors analysis,risk consequences ana-lysis,risk feedback loop identification and corresponding pre-control measures,and achieves a good risk identification effect.

Dynamic model and driving strategy of corporate social responsibility

Corporate social responsibility is the inevitable requirement for the survival and development of enterprises in modern society,as well as the basic guarantee for the sustainable development of economy and society.In order to analyze the driving factors of corporate social responsibility from both internal and external aspects,the dynamic model of corporate social responsibility was constructed,and the driving strategies of corporate social responsibility were also suggested.The driving factors of corporate social responsibility include not only the external constraints of policies,regulations and stakeholders,but also the internal requirements of the sustainable development of enterprises.Only when the external driving force is transformed into the spontaneous and conscious responsibility behavior of the enterprise,can the enterprise achieve its due effect.Moreover,in order to better fulfill the social responsibility,enterprise should build a management system of social responsibility,enhance the awareness of social responsibility,and promote the effective implementation of social responsibility projects.The relevant department should strengthen the all-round supervision of corporate social responsibility,and further improve the policies,laws and regulations related to social responsibility.Enterprises should strengthen communication with stakeholders,actively disclose social responsibility information,and constantly improve social responsibility behavior.By implementing social responsibility,enterprise can improve its business environment,enhance corporate brand image and core competitiveness,and promote the sustainable development of economy and society.

Multi-objective integrated optimization based on evolutionary strategy with a dynamic weighting schedule

The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.

Dynamic matrix encoding strategy for voice-over-IP steganography

In order to optionally regulate embedding capacity and embedding transparency according to user's requirements in voice-over-IP(VoIP) steganography,a dynamic matrix encoding strategy(DMES) was presented.Differing from the traditional matrix encoding strategy,DMES dynamically chose the size of each message group in a given set of adoptable message sizes.The appearance possibilities of all adoptable sizes were set in accordance with the desired embedding performance(embedding rate or bit-change rate).Accordingly,a searching algorithm that could provide an optimal combination of appearance possibilities was proposed.Furthermore,the roulette wheel algorithm was employed to determine the size of each message group according to the optimal combination of appearance possibilities.The effectiveness of DMES was evaluated in StegVoIP,which is a typical covert communication system based on VoIP.The experimental results demonstrate that DMES can adjust embedding capacity and embedding transparency effectively and flexibly,and achieve the desired embedding performance in any case.For the desired embedding rate,the average errors are not more than 0.000 8,and the standard deviations are not more than 0.002 0;for the desired bit-change rate,the average errors are not more than 0.001 4,and the standard deviations are not more than 0.002 6.

Optimization of dynamic sequential test strategy for equipment health management

Testing is the premise and foundation of realizing equipment health management （EHM）. To address the problem that the static periodic test strategy may cause deficient test or excessive test, a dynamic sequential test strategy （DSTS） for EHM is presented. Considering the situation that equipment health state is not completely observable in reality, a DSTS optimization method based on partially observable semi-Markov decision pro- cess （POSMDP） is proposed. Firstly, an equipment health state degradation model is constructed by Markov process, and the control limit maintenance policy is also introduced. Secondly, POSMDP is formulated in great detail. And then, POSMDP is converted to completely observable belief semi-Markov decision process （BSMDP） through belief state. The optimal equation and the corresponding optimal DSTS, which minimize the long-run ex- pected average cost per unit time, are obtained with BSMDP. The results of application in complex equipment show that the proposed DSTS is feasible and effective.

Solution of Chemical Dynamic Optimization Using the Simultaneous Strategies

An approach of simultaneous strategies with two novel techniques is proposed to improve the solution accuracy of chemical dynamic optimization problems. The first technique is to handle constraints on control vari- ables based on the finite-element collocation so as to control the approximation error for discrete optimal problems, where a set of control constraints at dement knots are integrated with the procedure for optimization leading to a significant gain in the accuracy of the simultaneous strategies. The second technique is to make the mesh refine- ment more feasible and reliable by introducing length constraints and guideline in designing appropriate element length boundaries, so that the proposed approach becomes more efficient in adjusting dements to track optimal control profile breakpoints and ensure accurate state and centrol profiles. Four classic benchmarks of dynamic op- timization problems are used as illustrations, and the proposed approach is compared with literature reports. The research results reveal that the proposed approach is preferz,ble in improving the solution accuracy of chemical dy- namic optimization problem.

A Scheme Library-Based Ant Colony Optimization with 2-Opt Local Search for Dynamic Traveling Salesman Problem

The dynamic traveling salesman problem(DTSP)is significant in logistics distribution in real-world applications in smart cities,but it is uncertain and difficult to solve.This paper proposes a scheme library-based ant colony optimization(ACO)with a two-optimization(2-opt)strategy to solve the DTSP efficiently.The work is novel and contributes to three aspects:problemmodel,optimization framework,and algorithmdesign.Firstly,in the problem model,traditional DTSP models often consider the change of travel distance between two nodes over time,while this paper focuses on a special DTSP model in that the node locations change dynamically over time.Secondly,in the optimization framework,the ACO algorithm is carried out in an offline optimization and online application framework to efficiently reuse the historical information to help fast respond to the dynamic environment.The framework of offline optimization and online application is proposed due to the fact that the environmental change inDTSPis caused by the change of node location,and therefore the newenvironment is somehowsimilar to certain previous environments.This way,in the offline optimization,the solutions for possible environmental changes are optimized in advance,and are stored in a mode scheme library.In the online application,when an environmental change is detected,the candidate solutions stored in the mode scheme library are reused via ACO to improve search efficiency and reduce computational complexity.Thirdly,in the algorithm design,the ACO cooperates with the 2-opt strategy to enhance search efficiency.To evaluate the performance of ACO with 2-opt,we design two challenging DTSP cases with up to 200 and 1379 nodes and compare them with other ACO and genetic algorithms.The experimental results show that ACO with 2-opt can solve the DTSPs effectively.

The dynamic metabolic profile of Qi-Yu-San-Long decoction in rat urine using UPLC-QTOF-MS^(E) coupled with a post-targeted screening strategy

Qi-Yu-San-Long decoction(QYSLD)is a traditional Chinese medicine that has been clinically used in the treatment of non-small-cell lung cancer(NSCLC)for more than 20 years.However,to date,metabolicrelated studies on QYSLD have not been performed.In this study,a post-targeted screening strategy based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight full information tandem mass spectrometry(UPLC-QTOF-MS^(E))was developed to identify QYSLD-related xenobiotics in rat urine.The chemical compound database of QYSLD constituents was established from previous research,and metabolites related to these compounds were predicted in combination with their possible metabolic pathways.The metabolites were identified by extracted ion chromatograms using predicted m/z values as well as retention time,excimer ions,and fragmentation behavior.Overall,85 QYSLD-related xenobiotics(20 prototype compounds and 65 metabolites)were characterized from rat urine.The main metabolic reactions and elimination features of QYSLD included oxidation,reduction,decarboxylation,hydrolysis,demethylation,glucuronidation,sulfation,methylation,deglycosylation,acetylation,and associated combination reactions.Of the identified molecules,14 prototype compounds and 58 metabolites were slowly eliminated,thus accumulating in vivo over an extended period,while five prototypes and two metabolites were present in vivo for a short duration.Furthermore,one prototype and five metabolites underwent the process of“appearing-disappearing-reappearing”in vivo.Overall,the metabolic profile and characteristics of QYSLD in rat urine were determined,which is useful in elucidating the active components of the decoction in vivo,thus providing the basis for studying its mechanism of action.

Dynamic Flow Control Strategies of Vehicle SCR Urea Dosing System

Selective Catalyst Reduction（SCR）Urea Dosing System（UDS）directly affects the system accuracy and the dynamic response performance of a vehicle.However,the UDS dynamic response is hard to keep up with the changes of the engine＇s operating conditions.That will lead to low NO_χconversion efficiency or NH_3 slip.In order to optimize the injection accuracy and the response speed of the UDS in dynamic conditions,an advanced control strategy based on an air-assisted volumetric UDS is presented.It covers the methods of flow compensation and switching working conditions.The strategy is authenticated on an UDS and tested in different dynamic conditions.The result shows that the control strategy discussed results in higher dynamic accuracy and faster dynamic response speed of UDS.The inject deviation range is improved from being between-8%and 10%to-4%and 2%and became more stable than before,and the dynamic response time was shortened from 200 ms to 150 ms.The ETC cycle result shows that after using the new strategy the NH_3 emission is reduced by 60%,and the NO_χemission remains almost unchanged.The trade-off between NO_χconversion efficiency and NH_3 slip is mitigated.The studied flow compensation and switching working conditions can improve the dynamic performance of the UDS significantly and make the UDS dynamic response keep up with the changes of the engine＇s operating conditions quickly.

Multi-Strategy Dynamic Spectrum Access in Cognitive Radio Networks: Modeling, Analysis and Optimization

Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA(MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain(CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.

MTCR-CR Routing Strategy for Connection-Oriented Routing over Satellite Networks

The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network.DT-DVTR in the snapshot-based connectionoriented routing strategy is one of the representative solutions,but it still has room for improvement in terms of routing stability.In this paper,we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules(MTCR-CR).The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL)construction solutions that meet the minimum number of topology changes to avoid route oscillations.The simulation results in Beidou-3 show that compared with DT-DVTR,MTCR-CR reduces the number of routing changes by about 92%,the number of path changes caused by routing changes is about38%,and the rerouting time is reduced by approximately 47%.At the same time,in order to show our algorithm more comprehensively,the same experimental index test was also carried out on the Globalstar satellite constellation.

A Predictive Energy Management Strategies for Mining Dump Trucks

The plug-in hybrid vehicles(PHEV)technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks.Meanwhile,plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies(EMS).Therefore,a series hybrid system is constructed based on a 100-ton mining dump truck in this paper.And inspired by the dynamic programming(DP)algorithm,a predictive equivalent consumption minimization strategy(P-ECMS)based on the DP optimization result is proposed.Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm,the P-ECMS strategy performs real-time stage parameter optimization to obtain the optimal equivalent factor(EF).Finally,applying the equivalent consumption minimization strategy(ECMS)realizes real-time control.The simulation results show that the equivalent fuel consumption of the P-ECMS strategy under the experimentally collected mining cycle conditions is 150.8 L/100 km,which is 10.9%less than that of the common CDCS strategy(169.3 L/100 km),and achieves 99.47%of the fuel saving effect of the DP strategy(150 L/100 km).

MULTI-CHANNEL TRANSMISSION STRATEGY FOR DYNAMIC SPECTRUM ACCESS

Cognitive radio is a promising technology that deals with the scarcity of radio spectrum. In this paper, we propose a new multi-channel transmission strategy for dynamic spectrum access in cognitive radio network. Starting with the model of spectrum activities, we present the multi-channel transmission strategy which has primary user's protection mechanism to improve the spectrum efficiency and study its performance under perfect and imperfect sensing. Numerical example results reveal that the performance of the proposed strategy has the superiority with respect to capacity performance of cognitive users and the protection of primary users.

A Control Strategy for Multi-Robot System Navigating in a Dynamic Environment

This paper introduces a new control strategy for heterogeneous multi-robots systems dedicated to industrial logistic setups. This control strategy is based on both distributed intelligence and machine learning and involves three parts: the rigid formation controller, the perception system and the path planner. Our controller is event-based and thus its control-coordination strategy can be self-adaptive and applied to real dynamic environment. During the navigating process, the multi-robots system derives the environment model, performs the path planning process that guaranties both the transportation constraints and the obstacle avoidance. For the validation, both simulation and real robot experiments are performed. The results show that the developed control strategy can be well used for realistic logistics applications.

Control strategy optimization using dynamic programming method for synergic electric system on hybrid electric vehicle

Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rules are derived from analyzing the optimal trajectories, and it has the highest contribution to Hybrid Electric Vehicle (HEV). The methods of how to get the best performance is also educed. Using the new Rule-based power management strat-egy adopted from the optimal results, it is easy to demonstrate the effectiveness of the new strategy in further improvement of the fuel economy by the synergic hybrid system.

Dynamic capabilities-based strategy innovation： a theoretical framework and empirical studies in Chinese firms

Based on investigations of 112 Chinese firms and studies on foreign leading corporations, a theoretical framework of dynamic capabilities based strategy innovation (SI) is put forward. Several large firms in China winning through SI were studied empirically. This paper complements previous publications on the theories of innovation and strategy. This work's findings will be useful for managers interested in our approach, which highlights the importance of SI and focuses on and points out the major pitfalls in the innovation processes. Implementing the dynamic capabilities based strategy innovation can effectively cultivate and develop core competences of corporations. It is concluded that implementing SI is the only path for Chinese enterprise growth in the intensified competition in the knowledge economy.

The Dynamic Evaluation of Enterprise's Strategy Based on Rough Set Theory

This paper presents dynamic evaluation of enterprise's strategy which is suitable for dealing with the complex and dynamic problems of strategic evaluation. Rough Set Theory is a powerful mathematical tool to handle vagueness and uncertainty of dynamic evaluation. By the application of Rough Set Theory, this paper computes the significance and weights of each evaluation criterion and helps to lay evaluation emphasis on the main and effective criteria. From the reduced decision table,evaluators can get decision rules Which direct them to give judgment or suggestion of strategy. The whole evaluation process is decided by data, so the results are certain and reasonable.