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Gene expression programming (GEP) is a data driven evolutionary technique that is well suited to correlation mining of system components. With the rapid development of industry 4.0, the number of components in a complex industrial system has increased significantly with a high complexity of correlations. As a result, a major challenge in employing GEP to solve system engineering problems lies in computation efficiency of the evolution process. To address this challenge, this paper presents EGEP, an Event Tracker enhanced Gene Expression Programming which filters irrelevant system components to ensure the evolution process to converge quickly. Furthermore, we introduce three theorems to mathematically validate the effectiveness of EGEP based on Gene expression programming schema theory. Experiment results also confirm that EGEP outperforms Gene expression programming with a shorter computation time in evolution. ; European Union's Horizon 2020 research and innovation program; 10.13039/501100012166-National Basic Research Program of China (973 Program); 10.13039/501100003399-Science and Technology Commission of Shanghai Municipality;

Gene expression programming (GEP) is a data driven evolutionary technique that well suits for correlation mining. Parallel GEPs are proposed to speed up the evolution process using a cluster of computers or a computer with multiple CPU cores. However, the generation structure of chromosomes and the size of input data are two issues that tend to be neglected when speeding up GEP in evolution. To fill the research gap, this paper proposes three guiding principles to elaborate the computation nature of GEP in evolution based on an analysis of GEP schema theory. As a result, a novel data engineered GEP is developed which follows closely the generation structure of chromosomes in parallelization and considers the input data size in segmentation. Experimental results on two data sets with complementary features show that the data engineered GEP speeds up the evolution process significantly without loss of accuracy in data correlation mining. Based on the experimental tests, a computation model of the data engineered GEP is further developed to demonstrate its high scalability in dealing with potential big data using a large number of CPU cores. ; National Fundamental Research Program (973) of China; 10.13039/501100003399-Science and Technology Commission of Shanghai Municipality; European Union's Horizon 2020 research and innovation programme;

The Qufu project is a collaboration of Shandong University, Shandong Provincial Institute of Archeology, UCLA, University of Michigan, and University of Texas at Austin. Our fieldwork at Qufu is funded by the Henry Luce Foundation for East Asian Archeology Grant (UCLA), the Ministry of Education of China 111 Project Grant (Shandong University), the Cotsen Institute of Archeology, the UCLA Senate Faculty Research Grant, and financial support from the Shandong Provincial Institute of Archeology. ; Peer reviewed ; Postprint

Abstract. This work presents ground based ultra low frequency (ULF) electromagnetic field measurements in the frequency range 0.1–10 Hz from January 2007 to December 2008. In this time period a strong earthquake series hits the Wenchuan region with a main shock of magnitude MS = 8.0 on 12 May 2008. The Hebei ULF electromagnetic observation network includes eight observation stations in north China and the observation system named E-EM is employed to record the electric potential difference between two electrodes with an analog automatic real-time continuous pen recorder. First, weak electric signals appeared on 11 October 2007 at Ningjin station, most of which are with relative long periods ~0.4–3 s and unequal amplitudes ~0.5–20 mm. Then, similar signals appeared at Gaobeidian station at the end of October. Abnormal behavior with various time intervals appeared randomly and not every day. At the beginning of April 2008, one and a half months before the Wenchuan MS = 8.0 earthquake, the anomalies were gradually subject to an intensive increase mainly in Gaobeidian SN direction and Ningjin EW direction. The abnormal behavior appeared almost every day and the amplitudes of electric signals, with short periods of ~0.1–0.3 s, enhanced to ~3–30 mm. Qingxian station started to record marginally high frequency signals in SN and EW components in the middle of April. On 9 May, 3 days before the main shock, the amplitude of high frequency information increased sharply at the same time in two components at Gaobeidian station and the maximum amplitude was up to 70 mm, i.e. 1.3 mV m−1 for the electric field. This situation did not stop until 17 May, 5 days after the main event. However, this kind of climax phenomena did not happen at Ningjin station and Qingxian station. Then weak anomalous information lasted about four months again, and strong signals appeared again for a short time before several powerful aftershocks. It is the first time that an abnormity with so large an amplitude and so long a duration time in the observation history of this network though several strong earthquakes were recorded. Furthermore, no obvious interferences have been found during this period. So this event is possibly related to this shock although all these three stations are more than 1300 km away from the Wenchuan earthquake epicenter.

As one of the common natural disasters, drought is extremely destructive to agriculture. Drought has risen in recent years, so how to effectively monitor drought has become the focus of attention of relevant government departments. When drought occurs, irrigation measures will be taken in the irrigation district for drought resistance and disaster reduction. At this time, drought monitoring based on meteorological data and remote sensing index has certain limitations. Based on the surface temperature data of MODIS, this paper extracted the irrigation area information in the irrigated district, compared the drought monitoring results of irrigated area with those based on precipitation anomaly percentage and vegetation anomaly index, and analysed the importance of agricultural drought monitoring based on remote sensing of irrigated area. This paper considers that it is necessary to consider the distribution of the irrigated area when conducting drought monitoring in the irrigation district, it can improve the accuracy of agricultural monitoring, and it can provide the basis for government and agriculture and other related departments to manage water resources and formulate drought-resistance policies.