In high-tech informative warfare, the combat system-of-systems which become increasingly functional and complex can be abstracted as heterogeneous combat networks (HCNs). The operational capability index (OCI) formula is an important model to evaluate the performance of HCNs. To prevent the error of accepting wrong conclusions when using OCI model, the correctness and accuracy of the model should be substantiated before making critical decisions. Accordingly, this paper presents an integrated methodology of framework named operational capability index model validation based on characteristic topology analysis (OCVCT) for validating and testing the OCI model. In this framework, a concept named characteristic topology, which conforms to military rules and has the highest operational capability assessment, is put forward to replace the compact model as the validation candidate. To search for characteristic topology efficiently, we propose an improved genetic algorithm (GA) with the key-gene oriented crossover operator which considers the prior knowledge of combat networks and takes advantages of both binary and real encoding methods. A case study proves the effectiveness of OCVCT. Moreover, compared with two state-of-the-art and one classical GAs, the improved GA has superiority in convergence speed and reliability. The idea of OCVCT also has a potential application prospect for various evaluation model validations of combat networks. INDEX TERMS Operational capability index, model validation, characteristic topology, genetic algorithm, heterogeneous combat networks, operational chain.
At present, the prefabricated construction industry is in a situation of increasing types of prefabricated components and generally high production costs. A hybrid optimization model considering continuity and discreteness for the production of fabricated concrete members is established to minimize production costs through the analysis of the production characteristics of precast concrete members. Under the premise of fully considering the staffing constraints, process constraints, construction period constraints, process constraints, and special process time limits for component production, the production arrangement and staffing of the components are rationalized and optimized. A discrete differential evolution (DDE) algorithm is introduced for such NP-hard problems. The double genetic chromosome coding mode and the active scheduling decoding method are adopted. Based on the improved POX (Precedence Operation Crossover) cross-evolution method, the global evolution operation is carried out, and an interchange-based local search method and continuous work penalty mechanism are designed to find the global optimal solution. The experimental results verify the practicality and effectiveness of the optimization model and algorithm.
A novel, to the best of our knowledge, interrogation scheme based on an optoelectronic oscillator (OEO) with high sensitivity and high speed response for a fiber optical current sensor utilizing a reflective interferometer is proposed and experimentally demonstrated. Due to the Faraday effect, a magneto-optic phase shift induced by current variation is generated between two orthogonal light waves. The polarization-dependent properties of the Mach–Zehnder modulator are used to convert the magneto-optic phase shift into the phase difference between the optical carrier and sideband, which is then mapped to the oscillating frequency shift by closing an OEO loop. A high current sensitivity of 152.5 kHz/A with a range of 0–2.5 A is obtained in the experiment.
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