This paper proposes risk evaluation system of metro project bidding based on factors which the environment and process of metro project bidding involved. Then the paper uses the entropy value method to determine the weights of the index and adopts Fuzzy to evaluate risk management level of metro project bidding, which takes the vagueness and uncertainty into account with a combination of both methods. According to the evaluation results, the paper puts forward recommendations for improvement and verifies the feasibility of the evaluation model. KEYWORD: Bidding of Metro Project; Risk Management; Entropy Value Method; Fuzzy
A B S T R A C TThis paper describes the first Rice Algorithm chip set. It operates under laboratory conditions at 25 Msamples/sec independent of entropy or quantization (4..14 bits/pixel). The algorithm is lossless and adapts to changing entropy conditions making it suited for images. The algorithm requires no external RAM and compression performance exceeds that of DPCM with UNIX compress. The encoder can operate a t twice the decoding rate. In the laboratory, most encoder parts were fully functional a t 60 Msamples/sec; or 840 Mbits/sec at N=14. The chips have been fabricated in a 1.0 micron CMOS process and are 5mm on a side. I N T R O D U C T I O NThe chip set discussed in this paper' describes the first Rice Algorithm [I] chip set and is designed to perform high speed adaptive lossless compression and decompression. The Rice Algorithm was developed back in the early 1970s at Jet Propulsion Laboratory for use in deep space missions. Even though this algorithm may have appeared to lay dormant to those outside JPL, this chip set attains better compression performance on most images than using UNIX compress with DPCM.The major objective for designing and fabricating the chip set is to provide real time compression for satellites. In order to compress satellite imagery it must adapt rapidly to changing scene statistics and compress image data over a wide entropy range. Under nominal conditions (25C, 5.0V, nominal process) the encoder has been tested to be fully functional above 50 Msamples/sec and the decoder at 25 Msamples/sec. The chip set allows quantization from 4 bits through 14 bits/sample. At mazimum quantization, the encoder can compress data at a continuous rate of over 700 Mbits/second. The chip set also can be operated as a high speed entropy coder/decoder by bypassing the This research was supported in part by NASA under grant NAGW-1406.DPCM part of the chips. Entropy coders are sometimes used in lossy schemes for coding addresses and magnitudes of frequency bins. Both chips have been fabricated in a 1.0 micron CMOS process. R I C E A L G O R I T H M OVERVIEWThe Rice Algorithm is a lossless compression method that is efficient over a wide range of entropy conditions. The algorithm handles Merent entropy conditions by having multiple coders, each of which is tuned to compress data at a particular entropy range.Instead of guessing what lies ahead on the scanline or on adjacent lines, as do many compression techniques, this algorithm codes a block of pixels by each of the coders and then selects the output from the coder that does the best compression job.Compression is done on small blocks of pixels (16, for example). This allows excellent adaptation within a scanline. Using smaller blocks does increase the overhead due to the ID bits (identification bits) preceding each data block. The ID bits inform the decoder which of the coders won for that block.A block diagram of the Rice Algorithm is shown in Figure 1. In typical operation, the first encoding step is to save a reference pixel at the start of eve...
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