Operational readiness and mission availability are two important standards in equipment supportability. To evaluate these two standards, an improved particle swarm optimization (PSO) algorithm to solve the mixed integ...
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ISBN:
(纸本)9781479986477
Operational readiness and mission availability are two important standards in equipment supportability. To evaluate these two standards, an improved particle swarm optimization (PSO) algorithm to solve the mixed integer programming (MIP) problems has been developed. the augmented Lagrange multiplier method is employed to deal withthe constraints, and special update strategy employed to restrict the swarm particles to lies only in integer positions. Tests on the two former mathematical models have verified the effectiveness of the proposed mixed technique, and it can be easily applied to other mixed integer programming with Constraint problem.
A novel and simple combination of inductive logic programming with swarm intelligence is presented. the Ant-FOIL tightly integrates the well-known inductive logic programming rule-learner FOIL with Ant Colony System m...
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ISBN:
(纸本)9781479986477
A novel and simple combination of inductive logic programming with swarm intelligence is presented. the Ant-FOIL tightly integrates the well-known inductive logic programming rule-learner FOIL with Ant Colony System meta-heuristic. the hypotheses construction is guided by the ACS stochastic local decision policy depends on pheromone and heuristic information. Experiments in applying Ant-FOIL to well-known benchmarks shows that Ant-FOIL performs better than either its baseline algorithm (FOIL), and is at the same time competitive with more sophisticated approaches (kFOIL, nFOIL and Aleph).
We present JolokiaC++ a compiler framework to ease coding of irregular data applications on GPUs. the effectiveness of the compiler and runtime systems of JolokiaC++ is tested using three kernels IRREG, MOLDYN and NBF...
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We present JolokiaC++ a compiler framework to ease coding of irregular data applications on GPUs. the effectiveness of the compiler and runtime systems of JolokiaC++ is tested using three kernels IRREG, MOLDYN and NBF, executed on NVIDIA GPUs. We developed extensions for the generic parallel constructs that allow portable and efficient programming of codes with irregular accesses on the GPU. We present experimental results from compiling the kernels for execution on Fermi GTX 480, Tesla C1060 and Tesla K20c GPUs.
the Belief-Desire-Intention (BDI) model is well suited for describing an agent's mental state. To model human reasoning with uncertainty and imprecision, fuzzy logic have been employed to represent beliefs for BDI...
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ISBN:
(纸本)9781479986477
the Belief-Desire-Intention (BDI) model is well suited for describing an agent's mental state. To model human reasoning with uncertainty and imprecision, fuzzy logic have been employed to represent beliefs for BDI agents in our previous work. In order that the BDI agents are more and more suitable for modelling our real world, a BDI agent programming language with fuzzied-belief based on a existing BDI agent programming language is developed in this paper. the new language is more flexible and human-like compared to non-fuzzy based BDI agent language in the real world applications. Particularly, it provides a more reasonable planning selection mechanism. the reasoning capability of the previous BDI language is improved due to the work in this paper.
this paper aims to model system of ordinary differential equations by using a new hybrid gene expression programming algorithm. Gene expression programming is a recently developed evolutionary computation method for m...
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ISBN:
(纸本)9781479986477
this paper aims to model system of ordinary differential equations by using a new hybrid gene expression programming algorithm. Gene expression programming is a recently developed evolutionary computation method for model learning and knowledge discovery. the hybrid algorithm combined immune clonal selection algorithm and memetic algorithm with gene expression programming to find not only the structure of system of differential equations but also optimize its constant parameters. the idea of immune clone principle is incorporated into the evolution process to enhance the diversity of population and the memetic algorithm is introduced to improve the ability of local search. Experiments on benchmark problems have shown that the hybrid approach is able to provide highly competitive results compared withthat of conventional genetic programming applied to this problem.
this paper proposes an approach for optimal power flow considering several contingency states. Initially, contingency selection is conducted to measure how much a specific contingency may affect the operation cost. th...
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this paper proposes an approach for optimal power flow considering several contingency states. Initially, contingency selection is conducted to measure how much a specific contingency may affect the operation cost. then, some severe contingencies are incorporated into optimal power flow problem. All considered states, normal and contingency states, are simulated simultaneously. thus, if contingency occurs, it can be ensured that all constraints such as generation limit, transmission limit and ramp rate will be satisfied. To solve the problem, quadratic programming is applied. IEEE 30 bus system is used as test system to show the ability of the proposed approach.
In this paper, we develop a receding horizon control (RHC) approach to linear systems through a direct method using the Block Pulse Functions (BPFs) parameterizations technique. this approach is based on the online op...
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In this paper, we develop a receding horizon control (RHC) approach to linear systems through a direct method using the Block Pulse Functions (BPFs) parameterizations technique. this approach is based on the online optimal controls using BPFs and linear programming to formulate new control gains at every iteration. To update the gain, a linear programming algorithm was implemented in real-time for solving the optimal control problem. this approach is applied to real examples and simulations results showed meaningful improvement of the systems stability.
Significant recent effort in genetic programming has focused on selecting and combining candidate solutions according to a notion of behaviour defined in semantic space and has also highlighted disadvantages of relyin...
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ISBN:
(纸本)9781509019687
Significant recent effort in genetic programming has focused on selecting and combining candidate solutions according to a notion of behaviour defined in semantic space and has also highlighted disadvantages of relying on a single scalar measure to capture the complexity of program performance in evolutionary search. In this paper, we take an alternative, yet complementary approach which directs crossover in what we call adjudicated space, where adjudicated space represents an abstraction of program behaviour that focuses on the success or failure of candidate solutions in solving problem sub-components. We investigate the effectiveness of several possible adjudicated strategies on a variety of classification and symbolic regression problems, and show that both of our novel pillage and barter tactics significantly outperform both a standard genetic programming and an enhanced genetic programming configuration on the fourteen problems studied.
Security policy administrators face difficulties to ensure that the policies they specify in XACML correspond to what they intend to formulate and to understand their overall effect. this paper proposes a logic-based ...
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Security policy administrators face difficulties to ensure that the policies they specify in XACML correspond to what they intend to formulate and to understand their overall effect. this paper proposes a logic-based XACML3.0 analysis solution using Answer Set programming (ASP) where Ansprolog is used to model the XACML decision process and an ASP solver is employed in an innovative way to perform logical reasoning on access control policies such as detecting conflicts in a multi-organizational context.
Visual programming is widely used to allow users to create programs by manipulating program elements graphically rather than by specifying them textually. It is intuitive and effective. However, it has only just begun...
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Visual programming is widely used to allow users to create programs by manipulating program elements graphically rather than by specifying them textually. It is intuitive and effective. However, it has only just begun to be used in robotic programming. For example, in the Robot Operating System (ROS) - a popular framework used for developing robotic applications - in order to run multiple modules together, a ROS launch file needs to be created and used. the files are in XML format and are difficult to write and understand for nontechnical users. To address this problem, in this paper, we propose a visual programming software tool that helps in the creation and visualization of these ROS launch files. this tool enables non-experienced operators to program a robot at a modular level. the tool is one among a set of software tools in the Robot Application Development and Operating Environment (RADOE), which aims to ease the development of robot applications in ROS.
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