A Doubleton Pattern Mining Approach for Discovering Colossal Patterns from Biological Dataset

Prasanna, K.; Seetha, M.

doi:10.5120/21364-4386

Cited by 6 publications

(3 citation statements)

References 11 publications

(8 reference statements)

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“…Where: a represents the weight of the learner, and the weight calculation method is the same as that of ADA boost weak classifier. In Ada Boost, the error rate represents the proportion of samples with classification errors in the total samples [22,23]. However, in the mining problem, the error rate C is used to represent the global error in the current learner, and φ is set to represent the number of scores in the training set, then Eq (14) calculates C:…”

Section: Plos Onementioning

confidence: 99%

Mining algorithm of accumulation sequence of unbalanced data based on probability matrix decomposition

Mou

Zhang

2023

PLoS ONE

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Due to the inherent characteristics of accumulation sequence of unbalanced data, the mining results of this kind of data are often affected by a large number of categories, resulting in the decline of mining performance. To solve the above problems, the performance of data cumulative sequence mining is optimized. The algorithm for mining cumulative sequence of unbalanced data based on probability matrix decomposition is studied. The natural nearest neighbor of a few samples in the unbalanced data cumulative sequence is determined, and the few samples in the unbalanced data cumulative sequence are clustered according to the natural nearest neighbor relationship. In the same cluster, new samples are generated from the core points of dense regions and non core points of sparse regions, and then new samples are added to the original data accumulation sequence to balance the data accumulation sequence. The probability matrix decomposition method is used to generate two random number matrices with Gaussian distribution in the cumulative sequence of balanced data, and the linear combination of low dimensional eigenvectors is used to explain the preference of specific users for the data sequence; At the same time, from a global perspective, the AdaBoost idea is used to adaptively adjust the sample weight and optimize the probability matrix decomposition algorithm. Experimental results show that the algorithm can effectively generate new samples, improve the imbalance of data accumulation sequence, and obtain more accurate mining results. Optimizing global errors as well as more efficient single-sample errors. When the decomposition dimension is 5, the minimum RMSE is obtained. The proposed algorithm has good classification performance for the cumulative sequence of balanced data, and the average ranking of index F value, G mean and AUC is the best.

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Section: Plos Onementioning

confidence: 99%

Mining algorithm of accumulation sequence of unbalanced data based on probability matrix decomposition

Mou

Zhang

2023

PLoS ONE

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“…Wire lengths have been cut by half, or even by 10%, in some situations, in order to save money. In [18], Rent's criteria for determining interconnection power consumption were applied to determine interconnection power consumption. When compared to area streamlined circuits, power consumption is reduced by 72.9 percent overall, with 44.4 percent zone overhead.…”

Section: Review Of Literaturementioning

confidence: 99%

Perimeter Degree Technique for the Reduction of Routing Congestion during Placement in Physical Design of VLSI Circuits

Lakshmanna

Shaik²,

Gunjan³

et al. 2022

Complexity

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When used in conjunction with the current floorplan and the optimization technique in circuit design engineering, this research allows for the evaluation of design parameters that can be used to reduce congestion during integrated circuit fabrication. Testing the multiple alternative consequences of IC design will be extremely beneficial in this situation, as will be demonstrated further below. If the importance of placement and routing congestion concerns is underappreciated, the IC implementation may experience significant nonlinear problems throughout the process as a result of the underappreciation of placement and routing congestion concerns. The use of standard optimization techniques in integrated circuit design is not the most effective strategy when it comes to precisely estimating nonlinear aspects in the design of integrated circuits. To this end, advanced tools such as Xilinx VIVADO and the ICC2 have been developed, in addition to the ICC1 and VIRTUOSO, to explore for computations and recover the actual parameters that are required to design optimal placement and routing for well-organized and ordered physical design. Furthermore, this work employs the perimeter degree technique (PDT) to measure routing congestion in both horizontal and vertical directions for a silicon chip region and then applies the technique to lower the density of superfluous routing (DSR) (PDT). Recently, a metaheuristic approach to computation has increased in favor, particularly in the last two decades. It is a classic graph theory problem, and it is also a common topic in the field of optimization. However, it does not provide correct information about where and how nodes should be put, despite its popularity. Consequently, in conjunction with the optimized floorplan data, the optimized model created by the Improved Harmonic Search Optimization algorithm undergoes testing and investigation in order to estimate the amount of congestion that occurs during the routing process in VLSI circuit design and to minimize the amount of congestion that occurs.

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“…In [17], the authors projected a developmental calculation known as craziness-based PSO for streamlining the floor arranging of a VLSI chip. It was utilized to accelerate nearby inquiries and improve the exactness of the arrangement.…”

Section: Related Workmentioning

confidence: 99%

An Improved Harmony Search Approach for Block Placement for VLSI Design Automation

Karimullah

Vishnuvardhan

Bhaskar

2022

Wireless Pers Commun

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The technology grows quickly in the area of the VLSI physical design; it is crucial to integrate the greater number of transistors and parts into a very small range. Before the placement is completed, the physical and technical positioning of the blocks in the chip area is planned, which is nothing but floor planning. In order to lessen the placement region in the physical layout, floor planning must be carried out effectively. This paper proposes a blended harmony search and particle swarm optimization (BHSPS) algorithm which is the deliberate blend of the harmony search (HS) algorithm, and the particle swarm optimization (PSO) algorithm is proposed to acquire the central goal of the VLSI placement strategy. The objective here is to lessen the field of plan. The MATLAB code for the blended harmony search and particle swarm optimization (BHSPS) algorithm is compiled, and investigations were carried out for better examination through the standard MCNC, i.e., North Carolina Microelectronics Center benchmark circuits.

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A Doubleton Pattern Mining Approach for Discovering Colossal Patterns from Biological Dataset

Cited by 6 publications

References 11 publications

Mining algorithm of accumulation sequence of unbalanced data based on probability matrix decomposition

Mining algorithm of accumulation sequence of unbalanced data based on probability matrix decomposition

Perimeter Degree Technique for the Reduction of Routing Congestion during Placement in Physical Design of VLSI Circuits

An Improved Harmony Search Approach for Block Placement for VLSI Design Automation

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