With the rapid development of its national economy,China has become a major producer and consumer of energy.To guarantee the sustainable development of power industry and national economy,China should exploit fossil a...With the rapid development of its national economy,China has become a major producer and consumer of energy.To guarantee the sustainable development of power industry and national economy,China should exploit fossil and renewable energy efficiently according to the development situation of generation resources.Firstly,this paper analyzes the utilization status of main generation resources in China,such as coal,hydropower and wind energy.Secondly,this paper illustrates the STEP model,which analyzes some issues for China’s generation resource utilization from political,economic,social and technological aspects.For example,the resource distribution is inconsistent with electricity demand,the renewable energy power output is intermittent,and there is some disruption in coal mining.Finally,combined with the utilization status and issues,this paper presents some improvement approaches from the perspectives of cost,efficiency and external influence.展开更多
The integration of network reconfiguration and distributed generation(DG)can enhance the performances of overall networks.Thus,proper sizing and siting of DG need to be determined,otherwise it will cause degradation i...The integration of network reconfiguration and distributed generation(DG)can enhance the performances of overall networks.Thus,proper sizing and siting of DG need to be determined,otherwise it will cause degradation in system performance.However,determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space.This search space mostly contains non-radial network configurations.Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution.To reduce the searching complexity,this paper considers the discretized network reconfiguration via dataset approach.Water cycle algorithm(WCA)is used to obtain the near optimal solution of network reconfiguration,and sizing and sitting of DG.In addition,the power factor of DG is also optimized to reduce the power loss.The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor.The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima.The proposed method outperforms other technique such as harmony search algorithm(HSA),fireworks algorithm(FWA),Cuckoo search algorithm(CSA)and uniform voltage distribution based constructive algorithm(UVDA)and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20%and 27.88%,respectively.展开更多
In recent years, the metro system has advanced into an efficient transport system and become the mainstay of urban passenger transport in many mega-cities. Passenger flow is the foundation of making and coordinating o...In recent years, the metro system has advanced into an efficient transport system and become the mainstay of urban passenger transport in many mega-cities. Passenger flow is the foundation of making and coordinating operation plans for the metro system, and therefore, a variety of studies were conducted on transit assignment models. Nevertheless route choice sets of passengers also play a paramount role in flow estimation and demand prediction. This paper first discusses the main route constraints of which the train schedule is the most important, that distinguish rail networks from road networks. Then, a two-step approach to generate route choice set in a metro network is proposed. Particu- larly, the improved approach introduces a route filtenng with train operational information based on the conventional method. An initial numerical test shows that the proposed approach gives more reasonable route choice sets for scheduled metro networks, and, consequently, obtains more accurate results from passenger flow assignment. Recommendations for possible opportunities to apply this approach to metro operations are also provided, including its integration into a metro passenger flow assignment and simulation system in practice to help metro authorities provide more precise guidance information for passengers to travel.展开更多
Antiviral software systems (AVSs) have problems in identifying polymorphic variants of viruses without explicit signatures for such variants. Alignment-based techniques from bioinformatics may provide a novel way to g...Antiviral software systems (AVSs) have problems in identifying polymorphic variants of viruses without explicit signatures for such variants. Alignment-based techniques from bioinformatics may provide a novel way to generate signatures from consensuses found in polymorphic variant code. We demonstrate how multiple sequence alignment supplemented with gap penalties leads to viral code signatures that generalize successfully to previously known polymorphic variants of JS. Cassandra virus and previously unknown polymorphic variants of W32.CTX/W32.Cholera and W32.Kitti viruses. The implications are that future smart AVSs may be able to generate effective signatures automatically from actual viral code by varying gap penalties to cover for both known and unknown polymorphic variants.展开更多
Software testing has been attracting a lot of attention for effective software development.In model driven approach,Unified Modelling Language(UML)is a conceptual modelling approach for obligations and other features ...Software testing has been attracting a lot of attention for effective software development.In model driven approach,Unified Modelling Language(UML)is a conceptual modelling approach for obligations and other features of the system in a model-driven methodology.Specialized tools interpret these models into other software artifacts such as code,test data and documentation.The generation of test cases permits the appropriate test data to be determined that have the aptitude to ascertain the requirements.This paper focuses on optimizing the test data obtained from UML activity and state chart diagrams by using Basic Genetic Algorithm(BGA).For generating the test cases,both diagrams were converted into their corresponding intermediate graphical forms namely,Activity Diagram Graph(ADG)and State Chart Diagram Graph(SCDG).Then both graphs will be combined to form a single graph called,Activity State Chart Diagram Graph(ASCDG).Both graphs were then joined to create a single graph known as the Activity State Chart Diagram Graph(ASCDG).Next,the ASCDG will be optimized using BGA to generate the test data.A case study involving a withdrawal from the automated teller machine(ATM)of a bank was employed to demonstrate the approach.The approach successfully identified defects in various ATM functions such as messaging and operation.展开更多
基金support by the National Natural Science Foundation of China(No.71273090)Fundamental Research Funds for the Central Universities(No.2015XS44)
文摘With the rapid development of its national economy,China has become a major producer and consumer of energy.To guarantee the sustainable development of power industry and national economy,China should exploit fossil and renewable energy efficiently according to the development situation of generation resources.Firstly,this paper analyzes the utilization status of main generation resources in China,such as coal,hydropower and wind energy.Secondly,this paper illustrates the STEP model,which analyzes some issues for China’s generation resource utilization from political,economic,social and technological aspects.For example,the resource distribution is inconsistent with electricity demand,the renewable energy power output is intermittent,and there is some disruption in coal mining.Finally,combined with the utilization status and issues,this paper presents some improvement approaches from the perspectives of cost,efficiency and external influence.
基金supported by University of Malaya under faculty grant(No.GPF016A-2019).
文摘The integration of network reconfiguration and distributed generation(DG)can enhance the performances of overall networks.Thus,proper sizing and siting of DG need to be determined,otherwise it will cause degradation in system performance.However,determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space.This search space mostly contains non-radial network configurations.Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution.To reduce the searching complexity,this paper considers the discretized network reconfiguration via dataset approach.Water cycle algorithm(WCA)is used to obtain the near optimal solution of network reconfiguration,and sizing and sitting of DG.In addition,the power factor of DG is also optimized to reduce the power loss.The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor.The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima.The proposed method outperforms other technique such as harmony search algorithm(HSA),fireworks algorithm(FWA),Cuckoo search algorithm(CSA)and uniform voltage distribution based constructive algorithm(UVDA)and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20%and 27.88%,respectively.
基金financially supported by the National Science and Technology Support Program of China(2011BAG01B01)Program for Young Excellent Talents at Tongji University (2014KJ015)+1 种基金Shanghai Philosophy and Social Science Funds (2015EGL006)Fundamental Research Funds for the Central Universities of China(1600219249)
文摘In recent years, the metro system has advanced into an efficient transport system and become the mainstay of urban passenger transport in many mega-cities. Passenger flow is the foundation of making and coordinating operation plans for the metro system, and therefore, a variety of studies were conducted on transit assignment models. Nevertheless route choice sets of passengers also play a paramount role in flow estimation and demand prediction. This paper first discusses the main route constraints of which the train schedule is the most important, that distinguish rail networks from road networks. Then, a two-step approach to generate route choice set in a metro network is proposed. Particu- larly, the improved approach introduces a route filtenng with train operational information based on the conventional method. An initial numerical test shows that the proposed approach gives more reasonable route choice sets for scheduled metro networks, and, consequently, obtains more accurate results from passenger flow assignment. Recommendations for possible opportunities to apply this approach to metro operations are also provided, including its integration into a metro passenger flow assignment and simulation system in practice to help metro authorities provide more precise guidance information for passengers to travel.
文摘Antiviral software systems (AVSs) have problems in identifying polymorphic variants of viruses without explicit signatures for such variants. Alignment-based techniques from bioinformatics may provide a novel way to generate signatures from consensuses found in polymorphic variant code. We demonstrate how multiple sequence alignment supplemented with gap penalties leads to viral code signatures that generalize successfully to previously known polymorphic variants of JS. Cassandra virus and previously unknown polymorphic variants of W32.CTX/W32.Cholera and W32.Kitti viruses. The implications are that future smart AVSs may be able to generate effective signatures automatically from actual viral code by varying gap penalties to cover for both known and unknown polymorphic variants.
基金support from the Deanship of Scientific Research,University of Hail,Saudi Arabia through the project Ref.(RG-191315).
文摘Software testing has been attracting a lot of attention for effective software development.In model driven approach,Unified Modelling Language(UML)is a conceptual modelling approach for obligations and other features of the system in a model-driven methodology.Specialized tools interpret these models into other software artifacts such as code,test data and documentation.The generation of test cases permits the appropriate test data to be determined that have the aptitude to ascertain the requirements.This paper focuses on optimizing the test data obtained from UML activity and state chart diagrams by using Basic Genetic Algorithm(BGA).For generating the test cases,both diagrams were converted into their corresponding intermediate graphical forms namely,Activity Diagram Graph(ADG)and State Chart Diagram Graph(SCDG).Then both graphs will be combined to form a single graph called,Activity State Chart Diagram Graph(ASCDG).Both graphs were then joined to create a single graph known as the Activity State Chart Diagram Graph(ASCDG).Next,the ASCDG will be optimized using BGA to generate the test data.A case study involving a withdrawal from the automated teller machine(ATM)of a bank was employed to demonstrate the approach.The approach successfully identified defects in various ATM functions such as messaging and operation.
