Angle-modulated bat algorithm (AMBA) provides a technique that enables the bat algorithm (BA) developed for continuous problems to operate in binary spaces, which employs an angle modulation technique to generate a bit string corresponding to a binary problem solution and applies the BA to evolve the coefficients of the trigonometric generating function. However, there are some identified limitations of the original AMBA. This paper proposes a new AMBA variant called amplitude AMBA (A-AMBA). The A-AMBA is compared with the AMBA and several other binary heuristic algorithms on 13 classical benchmark functions and 12 zero-one knapsack problems. The obtained results indicate that the performance of this variant is superior to the AMBA in many problem cases. INDEX TERMS Angle modulation, bat algorithm, binary optimization, amplitude, zero-one knapsack problems.

Convolutional neural network (CNN) --the result of the training is affected by of initial

Quantum-behaved bat algorithm with mean best position directed (QMBA) is a novel variant of bat algorithm (BA) with good performance. However, the QMBA algorithm generates all stochastic coefficients with uniform probability distribution, which can only provide a relatively small search range, so it still faces a certain degree of premature convergence. In order to help bats escape from the local optimum, this article proposes a novel Gaussian quantum bat algorithm with mean best position directed (GQMBA), which applies Gaussian probability distribution to generate random number sequences. Applying Gaussian distribution instead of uniform distribution to generate random coefficients in GQMBA is an effective technique to promote the performance in avoiding premature convergence. In this article, the combination of QMBA and Gaussian probability distribution is applied to solve the numerical function optimization problem. Nineteen benchmark functions are employed and compared with other algorithms to evaluate the accuracy and performance of GQMBA. The experimental results show that, in most cases, the proposed GQMBA algorithm can provide better search performance.

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In the container transportation, RFID and GSM/CDMA technology applied to monitor import and export goods, which will make sure the security of goods in transportation. In this paper, the container monitoring security infrastructure is provided, which is combined by national custom monitoring center, port monitoring center and vessel monitoring center, in the security infrastructure, the searching algorithm is discussed. Keywords: Container Monitoring, Security infrastructure, RFID, station searching algorithm, GSM Ⅰ.INTRODUCTION As the rapid growing of container shipping, the real time track and management of container and goods has been gained more attention by researchers. Traditionally, the track and management of container is based on the image identifier techniques and manual data input. In this method, the information of container gathered by the video is transmitted into the information process center; the information of goods is entered into the information process center manually, it's lower identification speed, high error rate, and non-real time, and constrained the growing of world ocean shipping [1]. In recently years, the automatic RFID and GSM technology is provided in real time monitoring and research of container shipping. Ⅱ. RFID TECHNOLOGY Radio frequency identification (RFID) is an automatic identification technology, it identify and gather related data of the target by radio frequency. In general, RFID has three parts: 1) Tag: tag is an combination of coupling element and chips, every tag has a unique electronic code, used to identify object by attached to it, 2) Reader: the device of read tag, can handle or fixed, 3) Antenna: transmit the radio frequency signal between tag and reader.Electronic tag preserved the pre-defined formatted data, in practice application, electronic tag is attached to the surface of target, and the reader can identify the data saved in tag without contact, the information read from tag is sent to computer. RFID tag is classified by passive tag and active tag. The passive tag obtained work energy from magnetic fields yielded by reader, the reading or writing distance is short, lower cost. The active tag itself has battery, long read/write distance, bigger volume, higher cost compare to passive tag. The writing distance of tag is about 40%-80% of reading distance. What affect the RFID reading distance are the magnetic field yield by reader, induction sensitivity, and the capacity which the tag itself obtained energy and transmitted data.Reader transmit radio frequency signal by antenna, the tag yield induced current flow when it entered magnetic fields, then obtained energy and sent coded information, when the information is read by reader, information is decoded and sent to computer for further processing. In general, the frequency by which the reader transmit signal is the RFID working frequency, it has three spectrums: lower frequency (30khz-300khz), high frequency (3Mhz-30Mhz), and ultra high frequency (300MHz-3GHz), the normal working frequency is 125Khz, 134.2Kh...