A novel ANN fault diagnosis system for power systems using dual GA loops in ANN training

Fault diagnosis is of great importance to the rapid restoration of power systems. Many techniques have been employed to solve this problem. In this paper, a novel Genetic Algorithm (GA) based neural network for fault diagnosis in power systems is suggested, which adopts three-layer feed-forward neural network. Dual GA loops are applied in order to optimize the neural network topology and the connection weights. The first GA-loop is for structure optimization and the second one for connection weight optimization. Jointly they search the global optimal neural network solution for fault diagnosis. The formulation and the corresponding computer flow chart are presented in detail in the paper. Computer test results in a test power system indicate that the proposed GA-based neural network fault diagnosis system works well and is superior as compared with the conventional Back-Propagation (BP) neural network.published_or_final_versio

A novel radial basis function neural network for fault section estimation in transmission network

In this paper, the application of Radial Basis Function Neural Network (RBF NN) to fault section estimation in power systems is addressed. The orthogonal least square algorithm has been extended to optimize the parameters of RBF NN. In order to assess the effectiveness of RBF NN, a classical Back-Propagation Neural Network (BP NN) has been developed to solve the same problem for comparison. Computer test is conducted on a 4-bus test system and the test results show that the RBF NN is quite effective and superior to BP NN in fault section estimation.published_or_final_versio

Advanced Fault Section Estimation System for Power Networks Based on Hybrid Fuzzy System and Radial Basis Function Neural Network

Abstract Although the radial basis function neural network (RBF NN) offers a potential solution for fault section estimation (FSE) in power networks, it has to be totally retrained for the case of power network topology change or power network expansion and cannot provide any explanations for its diagnosis results due to the blackbox nature of the neural network. In this paper, the functional equivalence between RBF NN and fuzzy system (FS) is built up for FSE problem throughout the neural network training process. Furthermore, based on this point, a novel retraining strategy is presented for RBF NN, which can extract the unchanged knowledge from the original RBF NN and then insert the knowledge back to the new RBF NN about the changing part of the power network in the case of network topology change or expansion. The retraining strategy has been implemented and tested in a 4-bus power system. The simulation results show that the advanced FSE system with hybrid FS and RBF NN works successfully and efficiently in power networks.published_or_final_versio

Minimum degree reordering based graph partitioning method for distributed fault section estimation system in power networks

In order to make fault section estimation (FSE) in large-scale power networks use distributed artificial intelligence approach, we have to develop an efficient way to partition the large-scale power network into desired number of connected sub-networks such that each sub-network should have quasi-balanced working burden in performing FSE. In this paper, an efficient minimum degree reordering based graph partitioning method is suggested for the partitioning task. The method consists of two basic steps: partitioning the power network into connected, quasi-balanced and frontier minimized sub-networks based on minimum degree reordering and minimizing the number of the frontier nodes of the sub-networks through iterations so as to reduce the interaction of FSE in adjacent sub-networks. The partitioning procedure and characteristic analysis is presented. The method has been implemented with sparse storage technique and tested in the IEEE 14-bus, 30-bus and 118-bus systems respectively. Computer simulation results show that the proposed multiple-way graph partitioning method is suitable for FSE in large-scale power networks and is compared favorably with other graph partitioning methods suggested in references.published_or_final_versio

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Novel deformation-induced polymorphic crystallization and softening of Al-based amorphous alloys

© 2018 Acta Materialia Inc. Melt-spun amorphous ribbons of Al 90 Y 10 (at.%) (90Al) and Al 84 Y 8.5 Ni 4 Co 2 Pd 1 Fe 0.5 (84Al) are cold-rolled at near to liquid-nitrogen temperature or at room temperature, inducing partial crystallization to nanoscale fcc-Al (α-Al). The crystallization is characterized and contrasted with the distinct sequences of reactions on annealing 90Al and 84Al amorphous alloys. Rolling-induced crystallization leads to softening, opposite to the effect of nanocrystallization induced by annealing. The origins of the hardness changes are analyzed. The rolling induces novel polymorphic crystallization to α-Al with extended solid solubility. This transformation, which occurs equally in 84Al and 90Al, despite the much greater thermal stability of the former, allows the ribbons to retain good bending ductility, and delays the onset of embrittlement on subsequent annealing. Partial crystallization induced by cold-rolling is useful in avoiding the formation of compound phases associated with brittleness, and is a promising process for high-solute Al-based amorphous alloys to be further developed as structural materials

Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

Peer reviewe

Measurement of the t¯tZ and t¯tW cross sections in proton-proton collisions at √s=13 TeV with the ATLAS detector

A measurement of the associated production of a top-quark pair (t¯t) with a vector boson (W, Z) in proton-proton collisions at a center-of-mass energy of 13 TeV is presented, using 36.1  fb−1 of integrated luminosity collected by the ATLAS detector at the Large Hadron Collider. Events are selected in channels with two same- or opposite-sign leptons (electrons or muons), three leptons or four leptons, and each channel is further divided into multiple regions to maximize the sensitivity of the measurement. The t¯tZ and t¯tW production cross sections are simultaneously measured using a combined fit to all regions. The best-fit values of the production cross sections are σt¯tZ=0.95±0.08stat±0.10syst pb and σt¯tW=0.87±0.13stat±0.14syst pb in agreement with the Standard Model predictions. The measurement of the t¯tZ cross section is used to set constraints on effective field theory operators which modify the t¯tZ vertex

An integrated bioinformatics analysis reveals divergent evolutionary pattern of oil biosynthesis in high- and low-oil plants

Seed oils provide a renewable source of food, biofuel and industrial raw materials that is important for humans. Although many genes and pathways for acyl-lipid metabolism have been identified, little is known about whether there is a specific mechanism for high-oil content in high-oil plants. Based on the distinct differences in seed oil content between four high-oil dicots (20~50%) and three low-oil grasses (<3%), comparative genome, transcriptome and differential expression analyses were used to investigate this mechanism. Among 4,051 dicot-specific soybean genes identified from 252,443 genes in the seven species, 54 genes were shown to directly participate in acyl-lipid metabolism, and 93 genes were found to be associated with acyl-lipid metabolism. Among the 93 dicot-specific genes, 42 and 27 genes, including CBM20-like SBDs and GPT2, participate in carbohydrate degradation and transport, respectively. 40 genes highly up-regulated during seed oil rapid accumulation period are mainly involved in initial fatty acid synthesis, triacylglyceride assembly and oil-body formation, for example, ACCase, PP, DGAT1, PDAT1, OLEs and STEROs, which were also found to be differentially expressed between high- and low-oil soybean accessions. Phylogenetic analysis revealed distinct differences of oleosin in patterns of gene duplication and loss between high-oil dicots and low-oil grasses. In addition, seed-specific GmGRF5, ABI5 and GmTZF4 were predicted to be candidate regulators in seed oil accumulation. This study facilitates future research on lipid biosynthesis and potential genetic improvement of seed oil content

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at √s=7 TeV

Peer reviewe