Int. J. Model. Simul. Sci. Comput.最新文献_第6页

Survey on the investigation of forensic crime scene evidence 司法犯罪现场证据调查研究综述

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-28 DOI: 10.1142/s1793962322500477

Jyothi Johnson, R. Chitra

{"title":"Survey on the investigation of forensic crime scene evidence","authors":"Jyothi Johnson, R. Chitra","doi":"10.1142/s1793962322500477","DOIUrl":"https://doi.org/10.1142/s1793962322500477","url":null,"abstract":"Determining and proving that a specific person or several persons may or may not be there at the Crime Scene (CS) in every criminal investigation are vital. Thus, in the law enforcement community, more often the physical evidence is collected, preserved, and analyzed. The accused cannot be predicted by normal people or judge just by looking at the evidence obtained at the analysis phase. So, research studies were undertaken on automated recognition as well as retrieval system aimed at forensic Crime Scene Investigation (CSI). A survey on the investigation of forensic CS evidence is depicted here. The main focus is rendered on the computer-centered automated investigation system. The latest research on the different evidence-centered Forensic Investigation (FI), such as the face, Finger-Print (FP), shoeprint, together with other Foot-Wear (FW) impressions, Machine Learning (ML) algorithm-centered FI, ML-centered pattern recognition, features of disparate evidence in forensic CSI, and various matching technique-centered FI, is surveyed here. Finally, centered on the accuracy and other two metrics, the methods’ performance for CSI is compared. Out of all the other methods, OLBP + LSSVM produced better results for precision and recall followed by CLSTM. In terms of accuracy, CLSTM produced better results than any other method.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84944887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid intelligent modeling approach for online predicting and simulating surface temperature of HVs 高压汽车表面温度在线预测与模拟的混合智能建模方法

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-18 DOI: 10.1142/s1793962322410070

Ming Tie, Hong Fang, Jianlin Wang, Weihua Chen

{"title":"Hybrid intelligent modeling approach for online predicting and simulating surface temperature of HVs","authors":"Ming Tie, Hong Fang, Jianlin Wang, Weihua Chen","doi":"10.1142/s1793962322410070","DOIUrl":"https://doi.org/10.1142/s1793962322410070","url":null,"abstract":"Online prediction as well as online simulation of surface temperature will play a significant role in flight safety of future near space hypersonic vehicles (HVs). But it still remains a classical scientific problem both in thermodynamics and aerospace science. In view of the complex HV structure and complex heat conduction procedure, three-dimensional numerical simulation is too inefficient for online prediction, while current rapid computation methods cannot meet the requirement of accuracy. Therefore, a hybrid intelligent dynamic modeling approach is proposed to estimate the surface temperature of HV with the combination of mechanism equations, test data and intelligent modeling technology. A simplified model based on a mechanism equation and experimental formulas is presented for predicting or simulating transient heat conduction procedure efficiently, while a case-based reasoning (CBR) algorithm is developed to estimate two uncertain coefficients in the simplified model. Furthermore, a support vector regression (SVR)-based model is developed to compensate the modeling error. With the data both from high-precision finite element computation and from real-world HV thermal protection experiments, a number of comparative simulations demonstrate the effectiveness of the proposed hybrid intelligent modeling approach.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78428706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven modeling method with reverse process 数据驱动的逆向过程建模方法

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-17 DOI: 10.1142/s179396232341009x

Guo-dong Yi, Lifang Yi, Zaizhao Zhang, Chuihui Li

引用次数: 0

On the modeling of asymmetric disturbance effect and rejection control for fixed-wing aircraft 固定翼飞机非对称扰动效应建模及抗扰控制研究

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-12 DOI: 10.1142/s1793962322500362

Rui Li, Kaiyu Qin

引用次数: 0

Prediction of students' employability using clustering algorithm: A hybrid approach 用聚类算法预测学生就业能力:一种混合方法

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-12 DOI: 10.1142/s1793962322500490

N. Premalatha, S. Sujatha

{"title":"Prediction of students' employability using clustering algorithm: A hybrid approach","authors":"N. Premalatha, S. Sujatha","doi":"10.1142/s1793962322500490","DOIUrl":"https://doi.org/10.1142/s1793962322500490","url":null,"abstract":"Data Mining is a process of exploring the huge data in search of reliable patterns and methodical relationship among variables. As a result, the findings may be validated through applying the detected patterns to a novel subset of the data. In simple words, Data Mining is referred as extracting the useful information as large dataset and transforming into reliable structure for future use. Data Mining has shown its incredible performance in various fields to a greater extent, out of which, Educational Data Mining (EDM) is one among them. Many researchers have addressed huge number of problems in EDM and applied various techniques to reveal the useful and hidden information that helped in the process of decision making. Students getting employed during and after graduation are one of the important parts of their life. Students, based on their academic performances, are getting employed in companies they deserve. But still, the probability of getting employed is very less in this competitive world. In this paper, a real-time scenario has been chosen for analyzing various factors for getting employed/unemployed. Various clustering and classification techniques have been implemented and their performances are studied. A hybrid approach is presented in this paper that integrates the benefits of particle swarm optimization (PSO) and fuzzy clustering means (FCMs). The results obtained show that the proposed technique helps in obtaining higher accuracy to other clustering techniques. The proposed clustering algorithm PSO-FCM, accuracy is 34.4%, 36.45% and 28.45% higher than the existing method, time complexity shows 45%, 33% and 49% lower than the existing [Formula: see text]-means clustering, Naïve Bayes clustering and SVM clustering algorithms, respectively.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74765796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

GenMuNN: A mutation-based approach to repair deep neural network models 基于突变的修复深度神经网络模型的方法

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-12 DOI: 10.1142/s1793962323410088

Huanhuan Wu, Zheng Li, Zhanqi Cui, Jianbin Liu

{"title":"GenMuNN: A mutation-based approach to repair deep neural network models","authors":"Huanhuan Wu, Zheng Li, Zhanqi Cui, Jianbin Liu","doi":"10.1142/s1793962323410088","DOIUrl":"https://doi.org/10.1142/s1793962323410088","url":null,"abstract":"Deep neural network (DNN) models have been widely used in e-commerce, games, automobiles, manufacturing, and so on. Improper structure, parameters, activation function, or incorrect loss function of the DNN models may cause defects in performance or security. As a result, there are some researches that focus on repairing DNN such as MODE and Apricot. However, the cost of repairing is high or the repair may lead to overfitting. In order to solve this problem, we propose GenMuNN, which is a Mutation-Based Approach to Repair Deep Neural Network Models. First, it analyzes the importance of the weights of the neurons in each layer of the DNN model to the correctness of the final prediction results, and ranks the weights according to the influence on the prediction results of the DNN model. Second, mutation is performed to generate mutants based on the rank of weights, and genetic algorithms are used to select mutants for the next round of mutation until the stop condition is touched. Experiments are carried on a set of DNN models which are trained with the MNIST dataset. The experimental results show that GenMuNN can improve the accuracy of the DNN models.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85297624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Multi-objective rescue path optimization for passenger ship accident under tilt 客船倾斜事故多目标救援路径优化

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-12 DOI: 10.1142/s1793962322500520

Tengbin Zhu, Hao Zhang, Yingjie Xiao

{"title":"Multi-objective rescue path optimization for passenger ship accident under tilt","authors":"Tengbin Zhu, Hao Zhang, Yingjie Xiao","doi":"10.1142/s1793962322500520","DOIUrl":"https://doi.org/10.1142/s1793962322500520","url":null,"abstract":"In order to research the rescue path problem in the accident of passenger ships under tilt, this paper establishes a multi-objective rescue path optimization model under tilt effect. By analyzing the fuzzy time and fuzzy risk, the objective functions of this model are optimal satisfaction function and optimal risk function. Related constraints are also described mathematically. The PSO-GA (particle swarm and genetic) hybrid algorithm is used to solve the model when designing the algorithm. Two-level planning is incorporated in the algorithm, the best solution in the lower-level planning is assigned to the upper-level, and the upper-level plan feeds back the result to the lower level, and finally the global optimal Pareto solution is obtained. Decision makers can choose appropriate solutions based on their preference. The simulation experiment compares the multi-objective rescue path optimization model with the traditional time-optimal model. Among the three optimal solution sets, solution 1 decreases by 3.36% in risk and the satisfaction rate increases by 69.44%. Solution 2 rose by 13.96% in risk, but the satisfaction increased by 87.93%, and the risk of solution 3 decreased by 11.41%, while the satisfaction increased by 52.41%. The results show that the established model is reasonable and the algorithm is feasible.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74932699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Simulation-oriented model reuse in cyber-physical systems: A method based on constrained directed graph 面向仿真的网络物理系统模型复用:一种基于约束有向图的方法

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-08 DOI: 10.1142/s1793962322410057

Wenzheng Liu, Heming Zhang, Chao Tang, Shuangfei Wu, Hongguang Zhu

{"title":"Simulation-oriented model reuse in cyber-physical systems: A method based on constrained directed graph","authors":"Wenzheng Liu, Heming Zhang, Chao Tang, Shuangfei Wu, Hongguang Zhu","doi":"10.1142/s1793962322410057","DOIUrl":"https://doi.org/10.1142/s1793962322410057","url":null,"abstract":"Modeling and Simulation of Cyber-Physical Systems (MSCPS) is demanding in terms of immediate response to dynamic and complex changes of CPS. Simulation-oriented model reuse can be used to build a whole CPS model by reusing developed models in a new simulation application, which avoid repeated modeling and thus reduce the redevelopment of submodels. Model composition, one of the important methods, enables model reuse by selecting and adopting diversified integration solutions of simulation components to meet the requirements of simulation application systems. In this paper, a real-time model integration approach for global CPS modeling is proposed, which reuses developed submodels by compositing submodel nodes. Specifically, a constrained directed graph of submodels for the whole system which can meet the simulation requirements is constructed by reverse matching. Submodel properties, including co-simulation distance between submodel nodes, reuse benefit and simulation performance of model nodes, are quantified. Based on the properties, the model-integrated solution for the whole CPS simulation is retrieved throughout the model constrained digraph by the Genetic Algorithm (GA). In the experiment, the proposed method is applied to a typical model integrated computing scenario containing multiple model-integration solutions, among which the Pareto optimal solutions are retrieved. Results show that the effectiveness of the model integration method proposed in this paper is verified.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74136645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Regional importance detection of 3D mesh via fusion of local color difference and curvature entropy 基于局部色差和曲率熵融合的三维网格区域重要性检测

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-07 DOI: 10.1142/s179396232250060x

Xiaodong Wang, Fengju Kang, Hao Gu, Hongtao Liang

引用次数: 0

Coyote-Wolf optimization-based deep neural network for cancer classification using gene expression profiles 基于基因表达谱的基于狼-狼优化的深度神经网络癌症分类

Int. J. Model. Simul. Sci. Comput. Pub Date : 2022-03-07 DOI: 10.1142/s1793962322500581

M. K. Deshmukh, Vinod Vaze, A. Gaikwad

引用次数: 0