• Title/Summary/Keyword: probability theory

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GT-PSO- An Approach For Energy Efficient Routing in WSN

  • Priyanka, R;Reddy, K. Satyanarayan
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.17-26
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    • 2022
  • Sensor Nodes play a major role to monitor and sense the variations in physical space in various real-time application scenarios. These nodes are powered by limited battery resources and replacing those resource is highly tedious task along with this it increases implementation cost. Thus, maintaining a good network lifespan is amongst the utmost important challenge in this field of WSN. Currently, energy efficient routing techniques are considered as promising solution to prolong the network lifespan where multi-hop communications are performed by identifying the most energy efficient path. However, the existing scheme suffer from performance related issues. To solve the issues of existing techniques, a novel hybrid technique by merging particle swarm optimization and game theory model is presented. The PSO helps to obtain the efficient number of cluster and Cluster Head selection whereas game theory aids in finding the best optimized path from source to destination by utilizing a path selection probability approach. This probability is obtained by using conditional probability to compute payoff for agents. When compared to current strategies, the experimental study demonstrates that the proposed GTPSO strategy outperforms them.

SATURATED STRUCTURES FROM PROBABILITY THEORY

  • Song, Shichang
    • Journal of the Korean Mathematical Society
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    • v.53 no.2
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    • pp.315-329
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    • 2016
  • In the setting of continuous logic, we study atomless probability spaces and atomless random variable structures. We characterize ${\kappa}$-saturated atomless probability spaces and ${\kappa}$-saturated atomless random variable structures for every infinite cardinal ${\kappa}$. Moreover, ${\kappa}$-saturated and strongly ${\kappa}$-homogeneous atomless probability spaces and ${\kappa}$-saturated and strongly ${\kappa}$-homogeneous atomless random variable structures are characterized for every infinite cardinal ${\kappa}$. For atomless probability spaces, we prove that ${\aleph}_1$-saturation is equivalent to Hoover-Keisler saturation. For atomless random variable structures whose underlying probability spaces are Hoover-Keisler saturated, we prove several equivalent conditions.

AXIOMS FOR THE THEORY OF RANDOM VARIABLE STRUCTURES: AN ELEMENTARY APPROACH

  • Song, Shichang
    • Journal of the Korean Mathematical Society
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    • v.51 no.3
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    • pp.527-543
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    • 2014
  • The theory of random variable structures was first studied by Ben Yaacov in [2]. Ben Yaacov's axiomatization of the theory of random variable structures used an early result on the completeness theorem for Lukasiewicz's [0, 1]-valued propositional logic. In this paper, we give an elementary approach to axiomatizing the theory of random variable structures. Only well-known results from probability theory are required here.

Risk Assessment and Decision-Making of a Listed Enterprise's L/C Settlement Based on Fuzzy Probability and Bayesian Game Theory

  • Cheng, Zhang;Huang, Nanni
    • Journal of Information Processing Systems
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    • v.16 no.2
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    • pp.318-328
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    • 2020
  • Letter of Credit (L/C) is currently a very popular international settlement method frequently used in international trade processes amongst countries around the globe. Compared with other international settlement methods, however, L/C has some obvious shortcomings. Firstly, it is not easy to use due to the sophisticated processes its usage involves. Secondly, it is sometimes accompanied by a few risks and some uncertainty. Thus, highly efficient methods need to be used to assess and control these risks. To begin with, FAHP and KMV methods are used to resolve the problem of incomplete information associated with L/C and then, on this basis, Bayesian game theory is used in order to make more scientific and reasonable decisions with respect to international trade.

A study on the behavioral-structure of production activity through the statistical analysis models - focus on the probability distribution of PERT, Queueing theory - (통계적(統計的) 계량분석(計量分析)모델을 통한 생산활동(活動)의 행태구조(行態構造)에 관한 연구 -RERT와 Queueing theory의 확률분포를 중심으로-)

  • Kim, Hong Jae
    • Journal of Korean Society for Quality Management
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    • v.19 no.2
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    • pp.145-157
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    • 1991
  • Thid study intends to pursue behavioral-structure of production behavior through statistical models which are using in PERT and Queueing theory. We can corprehand the orders of human production behavior's characteristics by several related attributes of probablity/statistics. These attributes are poisson, Beta, exponential distributions and P.S Laplace's natural probability. Human production behavior is related and regressed to these attributes in many divisions intermediately. Progressive numerical understanding in many essential human behavior acts on the application of practical behavior standard in production word and operation.

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CO-CLUSTER HOMOTOPY QUEUING MODEL IN NONLINEAR ALGEBRAIC TOPOLOGICAL STRUCTURE FOR IMPROVING POISON DISTRIBUTION NETWORK COMMUNICATION

  • V. RAJESWARI;T. NITHIYA
    • Journal of applied mathematics & informatics
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    • v.41 no.4
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    • pp.861-868
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    • 2023
  • Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x(a,b)→ax2+bx2 = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

Moving Picture Compression for the Probability Entropy in 3D-DCT Frames. (3D -DCT 프레임간 확률 엔트로피에 의한 동영상 압축)

  • 박동춘;최재윤서경호김태효
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.863-866
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    • 1998
  • In this paper, we proposes Moving Picture Compression reducing bit numbers within the block by probability in 3D-DCT considered of temporal axis. From Delta Modification theory for frequency components, bit numbers within the block(4$\times$4) were properly compressed by using the Probability Entropy. At the result for the proposed algorithm, we could find that the values of PSNR for resolution and the compression rate were better than existing methods.

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A BAYESIAN METHOD FOR FINDING MINIMUM GENERALIZED VARIANCE AMONG K MULTIVARIATE NORMAL POPULATIONS

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • v.32 no.4
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    • pp.411-423
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    • 2003
  • In this paper we develop a method for calculating a probability that a particular generalized variance is the smallest of all the K multivariate normal generalized variances. The method gives a way of comparing K multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approach for the probability is intractable and thus a Bayesian method is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach. Necessary theory involved in the method and computation is provided.

Batch Size Distribution in Input Flow to Queues with Finite Buffer Affects the Loss Probability

  • Kim Che-Soong;Oh Young-Jin
    • Journal of Korea Society of Industrial Information Systems
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    • v.11 no.1
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    • pp.1-6
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    • 2006
  • Queueing models are good models for fragments of communication systems and networks, so their investigation is interesting for theory and applications. Theses queues may play an important role for the validation of different decomposition algorithms designed for investigating more general queueing networks. So, in this paper we illustrate that the batch size distribution affects the loss probability, which is the main performance measure of a finite buffer queues.

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