Due to the dispersive and multimode natures, only nonlinear Lamb waves with exact phase-velocity matching were generally used in previous studies to evaluate the evenly distributed microstructural evolution in the incipient stage of material degradation, because of the cumulative generation of second harmonics, which was also found within a significant propagation distance for mode pair S0-s0 with quasi phase-velocity matching at low frequency. To explore the feasibility of fatigue damage evaluation by using this mode pair and fully utilize its unique merits, the cumulative second harmonic analysis was performed on aluminum alloy specimens with various material damage produced by the continuous low cycle fatigue tests. Similar to mode pair S1-s2 with exact phase-velocity matching, a mountain shape curve between the normalized acoustic nonlinearity parameter and the fatigue life was also achieved with the peak point at about 0.65 fatigue life for mode pair S0-s0, even though a relatively higher sensitivity to fatigue damage was observed for mode pair S1-s2. The excited frequency selection was further analyzed in a certain frequency range, where the quasi phase-velocity matching condition was satisfied for mode pair S0-s0 owing to the less dispersive property. Results show that the fatigue damage can be effectively detected using the mode pair S0-s0, and a relatively lower excited frequency was preferred due to its higher sensitivity to microstructural evolution.

Accurate rainfall forecasting in watersheds is of indispensable importance for predicting streamflow and flash floods. This paper investigates the accuracy of several forecasting technologies based on Wavelet Packet Decomposition (WPD) in monthly rainfall forecasting. First, WPD decomposes the observed monthly rainfall data into several subcomponents. Then, three data-based models, namely Back-propagation Neural Network (BPNN) model, group method of data handing (GMDH) model, and autoregressive integrated moving average (ARIMA) model, are utilized to complete the prediction of the decomposed monthly rainfall series, respectively. Finally, the ensemble prediction result of the model is formulated by summing the outputs of all submodules. Meanwhile, these six models are employed for benchmark comparison to study the prediction performance of these conjunction methods, which are BPNN, WPD-BPNN, GMDH, WPD-GMDH, ARIMA, and WPD-ARIMA models. The paper takes monthly data from Luoning and Zuoyu stations in Luoyang city of China as the case study. The performance of these conjunction methods is tested by four quantitative indexes. Results show that WPD can efficiently improve the forecasting accuracy and the proposed WPD-BPNN model can achieve better prediction results. It is concluded that the hybrid forecast model is a very efficient tool to improve the accuracy of mid- and long-term rainfall forecasting.

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In order to enhance the anti-jamming capability of aeronautic swarm tactical network in the complicated electromagnetic environment, we address the problem of bandit-based cognitive anti-jamming strategy for enabling reliable information transmission. We first present an adversarial multiuser multi-armed bandit model for the aeronautic swarm network employing airborne cognitive radios with the same-frequency simultaneous transmit and receive feature. Then, we utilize the improved energy detection method to perform jamming sensing and derive the closed expression of false alarm probability, false detection probability, and the optimal decision threshold in the case of single and multi-jammer. Finally, using the jamming sensing output to calculate reward and with the objective of maximizing the throughput of each airborne radio, a decentralized selfish doubling trick kl-UCB ++ anti-jamming strategy is developed to allocate an optimal configuration of transmitting power and spectrum channel to each radio. This anytime bandit strategy is simultaneously minimaxed optimal and asymptotically optimal. The simulation results validate that the aggregate average throughput, cumulative regret obtained with the proposed anti-jamming strategy outperform the well-known UCB, kl-UCB ++ bandit algorithm. INDEX TERMS Cognitive anti-jamming, aeronautic swarm, adversarial multi-armed bandit, improved energy detection, doubling trick kl-UCB ++ .