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Optimization of water quality monitoring stations using dynamic programming approach, a case study of the Mond Basin Rivers, Iran

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ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY 2021年第2期23卷 2867-2881页

作者： Asadollahfardi, G. Heidarzadeh, N. Sekhavati, A. Asadi, M. Kharazmi Univ Dept Civil Engn Fac Engn Tehran Iran Univ Saskatchewan Coll Engn Dept Civil Geol & Environm Engn Saskatoon SK Canada

Due to the importance of reassessing water quality monitoring stations, we employed the performance of the dynamic programming approach (DPA) to locate the monitoring stations and their numbers at the Mond Basin Rivers, located in the south of Fars and Bushehr Province, Iran. Firstly, the present monitoring stations were classified and prioritized using the Strahler stream order system and geographic information system, and then, the objective function was developed in terms of irrigation and drinking purposes in the study area. The catchment area was broken into five subbasins, and each station separately was assigned a score between 10 and 90. The DPA showed a reduction in the existing stations from 16 to 12 for the irrigation concern and from 16 to 11 for drinking concern. The optimum number of stations in the study area was predicted to be 12 to satisfy the drinking and irrigation purposes together. The majority of retained stations were located in the southern part of the basin, which demonstrated that the river water quality conspicuously might be changed in comparison with the northern part. The compatibility between the DPA results, the ongoing catchment area situation and literature represented the suitability of DPA in optimizing the water quality monitoring stations and cutting redundant monitoring stations.

关键词： dynamic programming approach Mond Basin Rivers Sampling stations Strahler stream ordering

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Multi-stage timetable rescheduling for high-speed railways: a dynamic programming approach with adaptive state generation

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COMPLEX & INTELLIGENT SYSTEMS 2021年第3期7卷 1407-1428页

作者： Feng, Guoqi Xu, Peng Cui, Dongliang Dai, Xuewu Liu, Hui Zhang, Qi Northeastern Univ Sch Business Adm Shenyang 110169 Peoples R China Northeastern Univ Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China Ctr Natl Railway Intelligent Transportat Syst Eng Beijing 100081 Peoples R China

A dynamic programming (DP) approach with adaptive state generation and conflicts resolution is developed to address the timetable-rescheduling problem (TRP) at relatively lower computation costs. A multi-stage decision-making model is first developed to represent the timetable-rescheduling procedure in high-speed railways. Then, an adaptive state generation method by reordering the trains at each station is proposed to dynamically create the possible states according to the states of previous stages, such that the infeasible states can be removed and the search space is reduced. Then, conflicts are resolved by retiming the arrival and/or departure times of trains. Furthermore, the state transfer equation is built and Bellman equation is developed to derive the solution to minimize the total delay time (TT). A series of simulation experiments and a real-world case study are used to evaluate the performance of the proposed method. The simulation experiments indicate that the proposed method is able to find the optimal timetable with appropriate overtaking at right stations and reduce the total delay by 62.7% and 41.5% with respect to the First-Come-First-Serve (FCFS) and First-Schedule-First-Serve (FSFS) strategy that are widely used in practice. Comparing to the intelligent scheduling method (e.g., Ant Colony Optimization and Particle Swarm Optimization), similar objective performance can be achieved at a much lower cost of computation time, which make the proposed method more applicable to the TRP in daily operation of high-speed railway.

关键词： Multi-stage decision Rescheduling dynamic programming approach High-speed railway Adaptive state generation

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Timetable Mapping Model and dynamic programming approach for High-speed Railway Rescheduling 39

Timetable Mapping Model and Dynamic Programming Approach for...

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39th Chinese Control Conference (CCC)

作者： Xu, Peng Feng, Guoqi Cui, Dongliang Dai, Xuewu Zhang, Qi Chen, Feng Northeastern Univ Sch Business Adm Shenyang 110169 Peoples R China Northeastern Univ Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China Ctr Natl Railway Intelligent Transportat Syst Eng Beijing 100081 Peoples R China

ISBN: (纸本)9789881563903

In railway systems, rescheduling trains in case of delays or disruptions occur is a critical and challenging task to remain the punctuality of railway traffics. Solving the railway traffic rescheduling problem is complex, computation-intensive and time-consuming from practical and computational perspectives. The problem has typically a very large search space, making it time-consuming to solve even for state-of-the-art optimization solvers. In this paper, a dynamic programming (DP) approach is used to address the issues of high computation costs in rescheduling railways traffics under various delays, in order to map the arrival and departure time of the train to the state of DP, we develop a timetable mapping model for the real-time train rescheduling (TTR) problem. Each section is modeled as a stage in the action space and the state of each stage is represented by the departure sequence of all the trains at the station for timetable mapping. And we further obtain the state transfer equation and construct the Bellman equation with the goal of minimizing the total delay time and use the Bellman equation inverse to derive the solution. Finally, numerical experiments of TTR are conducted. The advantage of the proposed DP is illustrated from the perspective of the strategy compared with the widely used First-Come-First Serve (FCFS) and the First Schedule-First-Serve (FSFS). It shows that the proposed DP can effectively solve the TTR problems, especially for primary delay problems.

关键词： dynamic programming approach rescheduling high-speed railway timetable mapping

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A dynamic programming approach to Secure User Image Data in Cloud Based ERP Systems 5

A Dynamic Programming Approach to Secure User Image Data in ...

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5th International Conference on Image Information Processing (ICIIP)

作者： Mandal, Sudakshina Khan, Danish Ali Natl Inst Technol Dept Comp Applicat Jamshedpur Bihar India

ISBN: (纸本)9781728108995

Cloud based ERP systems are now used worldwide for better organizational control and management. Centralized access structure, high degree of availability and low platform dependence are some of key reasons for which the demand of using Cloud ERP runs high in the business market. All of the cloud ERPs provides enhanced security measures which make the data safe in cloud storage. However, insider threat is one the challenges that still hovers around the cloud based ERP systems. Since there are almost no security mechanism for stopping an insider of an organization who exploits the information by knowing all the security protocol, it becomes evident that user based information security in the cloud ERPs can be enhanced if confidential information itself remains concealed in a separate security envelope, opaque to even administrators. This paper presents an approach to protect confidentiality of user image data in cloud ERPs from such threats using image realization steganography. It aims to generate a secure, selectively reversible mapping scheme between a generic cover and a specific secret image data and store the secret-cover mapping in cloud storage. The mapping itself is of no use unless supplied with the suitable user specific key and therefore ensures security through obscurity. The approach is backed by reliable and verifiable experimental results.

关键词： Cloud Computing Cloud Storage Security Steganography dynamic programming approach Image Realization

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Timetable Mapping Model and dynamic programming approach for High-speed Railway Rescheduling

Timetable Mapping Model and Dynamic Programming Approach for...

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第三十九届中国控制会议

作者： Peng Xu Guoqi Feng Dongliang Cui Xuewu Dai Qi Zhang Feng Chen School of business administration Northeastern University Laboratory of Synthetical Automation for Process Industries Northeastern University The Center of National Railway Intelligent Transportation System Engineering and Technology

In railway systems,rescheduling trains in case of delays or disruptions occur is a critical and challenging task to remain the punctuality of railway *** the railway traffic rescheduling problem is complex,computation-intensive and time-consuming from practical and computational *** problem has typically a very large search space,making it time-consuming to solve even for state-of-the-art optimization *** this paper,a dynamic programming（DP）approach is used to address the issues of high computation costs in rescheduling railways traffics under various delays,in order to map the arrival and departure time of the train to the state of DP,we develop a timetable mapping model for the real-time train rescheduling（TTR） *** section is modeled as a stage in the action space and the state of each stage is represented by the departure sequence of all the trains at the station for timetable *** we further obtain the state transfer equation and construct the Bellman equation with the goal of minimizing the total delay time and use the Bellman equation inverse to derive the ***,numerical experiments of TTR are *** advantage of the proposed DP is illustrated from the perspective of the strategy compared with the widely used First-Come-First Serve（FCFS） and the First Schedule-First-Serve（FSFS）.It shows that the proposed DP can effectively solve the TTR problems,especially for primary delay problems.

关键词： dynamic programming approach rescheduling high-speed railway timetable mapping

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Optimal Control for Hybrid Energy Storage Electric Vehicle to Achieve Energy Saving Using dynamic programming approach

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ENERGIES 2019年第4期12卷 588页

作者： Pan, Chaofeng Liang, Yanyan Chen, Long Chen, Liao Jiangsu Univ Automot Engn Res Inst Zhenjiang 212013 Jiangsu Peoples R China Jiangsu Univ Coll Automot & Traff Engn Zhenjiang 212013 Jiangsu Peoples R China

In this paper, the efficiency characteristics of battery, super capacitor (SC), direct current (DC)-DC converter and electric motor in a hybrid power system of an electric vehicle (EV) are analyzed. In addition, the optimal efficiency model of the hybrid power system is proposed based on the hybrid power system component's models. A rule-based strategy is then proposed based on the projection partition of composite power system efficiency, so it has strong adaptive adjustment ability. Additionally. the simulation results under the New European Driving Cycle (NEDC) condition show that the efficiency of rule-based strategy is higher than that of single power system. Furthermore, in order to explore the maximum energy-saving potential of hybrid power electric vehicles, a dynamic programming (DP) optimization method is proposed on the basis of the establishment of the whole hybrid power system, which takes into account various energy consumption factors of the whole system. Compared to the battery-only EV based on simulation results, the hybrid power system controlled by rule-based strategy can decrease energy consumption by 13.4% in line with the NEDC condition, while the power-split strategy derived from the DP approach can reduce energy consumption by 17.6%. The results show that compared with rule-based strategy, the optimized DP strategy has higher system efficiency and lower energy consumption.

关键词： hybrid power system electric vehicle rule-based optimal strategy dynamic programming approach

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dynamic programming approach to visual place recognition in changing environments

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ELECTRONICS LETTERS 2017年第6期53卷 391-393页

作者： Oh, J. H. Lee, B. H. Seoul Natl Univ ASRI Dept Elect & Comp Engn 1 Gwanak Ro Seoul South Korea

Recognising places under extreme perceptual changes is a challenging problem. A new dynamic programming method to align sequences of image features extracted from a deep convolutional auto-encoder to efficiently solve this problem is proposed. As this method considers not only environmental variations, but also the motion constraint of the mobile robot, places from changing environment can be successfully recognised by finding the most likely path sequence. Experimental results show improved precision-recall performance compared with other algorithms.

关键词： dynamic programming feature extraction SLAM (robots) mobile robots robot vision dynamic programming approach visual place recognition image feature extraction deep convolutional autoencoder mobile robot precision-recall performance

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A dynamic programming approach to synchronize train timetables

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ADVANCES IN MECHANICAL ENGINEERING 2017年第6期9卷

作者： Tian, Xiaopeng Niu, Huimin Lanzhou Jiaotong Univ Sch Traff & Transportat Lanzhou 730070 Peoples R China

This article focuses on synchronizing timetables of train services at a rail transfer station. The main aim is to determine an optimal schedule of train services, given that the departure and arrival times of some particular trains are known. An exponential utility function is introduced to measure the synchronization levels between different train services. A nonlinear integer programming model is proposed to achieve the objective of a synchronized timetable. A dynamic programming approach is then designed to solve the developed model. Finally, a numerical example with real-world datasets is implemented to demonstrate the effectiveness of the proposed approaches.

关键词： Train timetable synchronization optimization dynamic programming approach

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A combined Convolutional Neural Network and dynamic programming approach for text line normalization 13

A combined Convolutional Neural Network and Dynamic Programm...

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13th IAPR International Conference on Document Analysis and Recognition (ICDAR)

作者： Pastor-Pellicer, Joan Espana-Boquera, Salvador Castro-Bleda, M. J. Zamora-Martinez, Francisco Univ Politecn Valencia Valencia Spain Univ CEU Cardenal Herrera Valencia Spain

ISBN: (纸本)9781479918058

This work proposes a new normalization algorithm for handwritten text lines based on the use of Convolutional Neural Networks trained to classify pixels of the scanned text line as belonging to the main body area. The reference lines of the text line are obtained from these local estimates by means of dynamic programming. The obtained reference lines are used to normalize the text line images. Experimental results on the IAM offline database demonstrates the feasibility of this approach.

关键词： dynamic programming handwritten character recognition image classification neural nets text detection visual databases IAM offline database convolutional neural network dynamic programming approach handwritten text lines local estimation pixel classification scanned text line text line image normalization text line normalization Hidden Markov models Image recognition Labeling Robustness dynamic programming Neural network handwritten character recognition visual databases Image recognition Hidden Markov models Image classification texts BASELINE normalization

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dynamic programming approach (DPA) for assessment of water quality network: a case study of the Sefied-Rud River

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WATER PRACTICE AND TECHNOLOGY 2014年第2期9卷 135-149页

作者： Asadollahfardi, G. Asadi, M. Nasrinasrabadi, M. Faraji, A. Kharazmi Univ Civil Engn Dept Tehran *** Iran

Due to financial constraints, water quality monitoring network design is an efficient way to manage water quality. The most crucial part is to find appropriate locations for monitoring stations. Considering the objectives of water usage, we evaluate existing water quality sampling stations of the Sefid-Rud River, located in the north of Iran, which has been used for irrigation and drinking water. There are several methods for assessment of existing monitoring stations such as Sanders method, multiple criteria decision making and dynamic programming approach (DPA) which DPA was opted in this study. The results showed that out of 21 existing monitoring stations, eight and seven stations should be retained on the upstream and downstream of the basins, respectively. Although the area of the downstream basin is larger than the upstream basin, the number of stations which was retained was less than upstream. This may mean that water quality of the downstream is more favorable than the upstream. Meanwhile the technique may be also suitable for optimization of the water quality network.

关键词： dynamic programming approach monitoring stations optimization the Sefid-Rud River water quality

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