International Journal of Intelligent Systems and Applications @ijisa
Статьи журнала - International Journal of Intelligent Systems and Applications
Все статьи: 1251
The Method of Measuring the Integration Degree of Countries on the Basis of International Relations
Статья научная
The paper studies the concept of integration, the integration of countries, basic characteristics of the integration of countries, the integration indicators of countries. The number of contacts between countries and the number of contracts signed between countries are offered as the indicators to determine the integration degree of countries. An approach to the design of the data warehouse for the decision support system in the field of foreign policy, using OLAP-technology is offered. Designed polycubic OLAP-model in which each cube is based on a separate data mart. Given the differences between the data warehouse and data mart. Shown that, one of the cubes of this model gives full information about the chosen indicators, including their aggregation on various parameters. Method for measuring the degree of integration of the countries, based on the calculation of the weight coefficients is proposed. In this regard, was described the information model of the relevant subsystem by using graph theory. Practical application of this method was shown. Moreover, the used software was shown.
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The Obstacle Detection and Measurement Based on Machine Vision
Статья научная
To develop a quick obstacle detection and measurement algorithm for the image-based autonomous vehicle (AV) or computer assisted driving system, this paper utilize the previous work of object detection to get the position of an obstacle and refocus windows on the selected target. Further calculation based on single camera will give the detailed measurement of the object, like the height, the distance to the vehicle, and possibly the width. It adopts a two camera system with different pitch angles, which can perform real-time monitoring for the front area of the vehicle with different coverage. This paper assumes that the vehicle will move at an even speed on a flat road, cameras will sample images at a given rate and the images will be analyzed simultaneously. Focus will be on the virtual window area of the image which is proved to be related to the distance to the object and speed of the vehicle. Counting of the blackened virtual sub-area can quickly find the existence of an obstacle and the obstacle area will be cut to get the interested parameter measurements for the object evaluation.
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The Research of Fuzzy Variable Transmission Ratio for Steer-by-wire System of Electric Forklift
Статья научная
Combining with the TE30 electric forklift produced by an enterprise, the principle of Steer-by-wire (SBW) system, steering motion state, ideal steering ratio are analyzed and studied. The biggest characteristic of SBW system is that the transmission ratio is free to design. Based on the establishment of two-degree-freedom linear model of Forklift, the paper designed the nonlinear transmission ratio function on vehicle speed and steering angle with the application of fuzzy control rules. The simulation results show that the fuzzy variable transmission ratio can make the yaw velocity gain tend to be constant, also can make Forklift light sensitive at low speeds and steady heavy at high speed. In order to ensure that the yaw velocity gain does not vary with the change of speed and steering angle, this paper presents a dynamic correction control strategy based on the steady-state control for Forklift. The simulation results show that the amplitudes of yaw velocity and sideslip angle are reduced with the dynamic correction of yaw velocity feedback, also the handling stability is improved.
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The Simulation Analysis of Nonlinear for a Power Amplifier with Memory Effects
Статья научная
For the nonlinear distortion problem of current power amplifiers (PAs) with memory effects, we use goal programming to present a memoryless predistorter matrix model based on limiting baseband predistortion technique, and the normalized mean squared error (NMSE) is limited in a satisfactory range while the output power is maximum. Then we propose a nonlinear power amplifier with memory effects based on back propagation neural network (BPNN) with three tapped delay nodes and six single hidden layer nodes, which is single input - dual output. Simulation results show that the method proposed in this paper makes the experimental precision higher. Further, the linearization effect of power amplifiers becomes better.
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The Study of Joint Acoustic Holography Algorithms based on Continuous Scanning
Статья научная
To effectively solve the problem of rapid measurement and recognition about large underwater sound source, continuous scanning is applied to measure the large underwater sound source. The theory of sound source recognition based on mobile framework technology (FAH)nd Helmholtz equation least squares method (HELS)s investigated. Combination of acoustic holography method based on MFAH and HELS is created and verified through simulation and basin test. The study shows that combination algorithm can accurately identify all kinds of underwater source and obtain a high positioning accuracy of the noise source, and can be used for a wide frequency range; when there are multiple coherent sound sources in the complex sound field, noise source identification and location only requires that an array holographic measurement surface is 1.3 times for the reconstruction surface. Using a small measuring surface to quickly identify large underwater sound source is achieved. The shortcomings of workload and time-consuming in the traditional measurement are resolved. And it provides convenience for engineering applications.
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Статья научная
This document presents two developed methods for solving the classification task of medical implant materials based on the compatible use of the Wiener Polynomial and SVM. The high accuracy of the proposed methodology for solving this task are experimentally confirmed. A comparison of the proposed methods with existing ones: Logistic Regression; Linear SVC; Random Forest; SVC (linear kernel); SVC (RBF kernel); Random Forest + Wiener Polynomial is carried out. The duration of training of all methods that described in work is investigated. The article presents the visualization of all method results for solving this task.
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The decision model for selection of tourism site using Analytic Network Process method
Статья научная
The criteria and sub criteria-based decision model for selection of tourism site using Analytic Network Process (ANP) method was to be implemented in Yogyakarta, Indonesia. In this study, we proposed criteria and sub criteria that influenced each other and had feedback between the two so that there was a comparison of tourism site alternatives according to sub criteria and pairwise comparative assessment with scale 1-9 that was then calculated in form of matrix of pairwise comparison. The result of this study was in form of decision alternatives in form of ranking to facilitate decision makers (DMs) in finding tourism sites.
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The information support of virtual research teams by means of cloud managers
Статья научная
The article deals with the creation of virtual research teams of scientists from various geographically distributed organizations united for joint interdisciplinary researches. Library social institutions are the satellites of virtual research teams and have to implement information and communication support of scientific researches. The use of cloud managers by academic libraries is proposed as platforms to facilitate remote collaborative work of the participants of the virtual research teams. The research of number of free cloud managers and their capabilities was held. The most successful cloud manager for supporting the scientific work of virtual research teams was selected by using hierarchy analysis method.
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Статья научная
The subject matter of the article is developing information and communication network (ICN) for critical infrastructure systems (CIS). The aim of the work is to provide high-quality information and telecommunication processes by developing the optimal version of distributing CIS functional tasks and ICN processes to the network nodes. The article deals with following problems: developing a model for mapping the information and technical ICN structures, developing a method for variant synthesis of ITS structural models, a formalized representation of the problem of selecting CIS optimal structure. The methods used are: the system method, the set-theoretic and graphic analytic approaches, methods of hierarchic structures synthesis, optimization methods. The following results were obtained: the use of system approach for formalizing the information processing process in CIS was justified; mapping the ICS functional system into the information and technical one was presented as multilevel graph chain; the generalized representation of graph structures hierarchy was developed for the set of data transmitting tasks; this approach enabled formal representing alternative variants that consider the main links, sequencing, the amount and flows of the processed information among the different structure levels; the scheme of variant synthesis method of ICN models according to graph structures mapping was developed; the problem of selecting optimal ICN structures was formally presented; a complex efficiency criterion for solving problems of optimizing variant synthesis of structures; the problem of optimal synthesis of the structure of the given level factored in resource constraints was formulated. Conclusions. The article deals with such novelty aspects as improving the model of problem of selecting the optimal ICN structure by set-theoretic formalization factored in the criterion of maximum intensity of computational resource application, which enabled determining structural links among the major elements considering the decomposition of the model up to the basic elements such as "node" and "task" and the development of a new method of optimal ICN structuring which unlike the existing ones involves the variant synthesis of structures hierarchy and formalizing selection problems on the basis of set-theoretic models, which enables providing the efficiency of application of information and technical net resources.
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The neurocontroller for satellite rotation
Статья научная
In this work an analysis of neurocontrollers is given. The purpose of this paper is the neurocontroler for attitude control: satellite rotations. The classification of neurocontroller architecture is provided. The pros and cons of different neurocontrollers are described. Two configuration of neural network – feedforward neural networks with mini-batch descent and modified Elman neural network, are investigated in this work to verify its ability to control the attitude of a satellite. The advantages and disadvantage of different predictive model neurorization systems are described. The class diagram for the simulating of satellite rotation for neural network learning is given. The proposed approach provides the architecture of the neural network and the weights among the layers in order to guarantee stability of the system. The accuracy was calculated. The AI module, after trained for different configurations of wheels, will get commands with desired 3D rotation speeds and control the wheels to achieve the desired rotation speeds.
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Theoretical Design and Computational Fluid Dynamic Analysis of Projectile Intake
Статья научная
With the development of the science and technology, the more requirements such as cost effective, high specific impulse in wide operation rang, becomes stricter and multiplicity. However, the existing supersonic inlet can no longer adjust to all the new projectiles. In this paper, based on the basic characteristic of inlet and considering the design requirements, the two-dimensional supersonic projectile inlet was designed and verified by numerical simulation under different operating conditions such as attack angle, altitude, and so on. The results are shown that: 1) The design process is successful, but the working conditions should be limited to the small angle of attack; 2) The total pressure recovery coefficient is increasing as the Ma number increases, and then is gradually decreased after the point of Mach number is equal to 0.5; 3) The existence of attack angle reduces values of total pressure recovery. And moreover, the shock wave which occurs at the anterior point is gradually deviating from projectile body direction with the increase of attack angle; 4). The variance ratio in the outlet has the acute changed with increasing of altitudes clearly, but its corresponding values degrade sharply in the entrance.
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Threshold controlled binary particle swarm optimization for high dimensional feature selection
Статья научная
Dimensionality reduction or the optimal selection of features is a challenging task due to large search space. Currently, many research has been performed in this domain to improve the accuracy as well as to minimize the computational complexity. Particle Swarm Optimization (PSO) based feature selection approach seems very promising and has been extensively used for this work. In this paper, a Threshold Controlled Binary Particle Swarm Optimization (TC-BPSO) along with Multi-Class Support Vector Machine (MC-SVM) is proposed and compared with Conventional Binary Particle Swarm Optimization (C-BPSO). TC-BPSO is used for the selection of features while MC-SVM is used to calculate the classification accuracy. 70% of the data is used to train the MC-SVM model while the test has been performed on rest 30% data to calculate the accuracy. Proposed approach is tested on ten different datasets having varying difficulties such as some datasets having large number of features while some have small, some have just two classes while some have many classes, some datasets having small number of instances while some have large number of instances and the results obtained on these datasets are compared with some of the existing methods. Experiments show that the obtained results are very promising and achieved the best accuracy in minimum possible features. Proposed approach outperforms C-BPSO in all contexts on most of the datasets and 3-4 times computationally faster. It also outperforms in all context when compared with the existing work and 5-8 times computationally faster.
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Time Series Forecasting Model Based on Discrete Grey LS-SVM
Статья научная
The advantages and disadvantages of discrete GM(1,1) model and least squares support vector machine are analyzed respectively, this article proposes a new time series forecasting model of discrete grey least squares support vector machine. The new model adopts structural risk minimization principle, at the same time develops the advantages of accumulation generation in the grey forecasting method, weakens the effect of stochastic-disturbing factors in original sequence, and avoids the theoretical defects existing in the grey forecasting model. The simulation results show that the forecasting model is effective and reliable, and consolidates the advantage of the discrete GM(1,1) model and least squares support vector machine. It offers a new way to improve the time series forecasting accuracy.
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Time Synchronization under 1PPS Signal in Distributed Real-time Simulation System
Статья научная
Time synchronization is one of the key points in distributed of a real-time simulation system. At first, a distributed simulation system is introduced. Secondly, time synchronization method under 1PPS signal is put forth. Thirdly, the relevant technology of time synchronization are studied, including system structure, SNTP, 1PPS signal and control logic. Vxworks watch dog timer mode and timecard counter mode under this method are also analyzed in detail and the precision is presented. Fourthly, Arena software is chosen to model and simulate the time synchronization procedure. At last, the whole simulation model is constructed and the experiment results are given out to prove the efficiency of the synchronization method.
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Статья научная
Time-frequency and time dependence of the output signal morphology of nonlinear oscillator neuron based on Van der Pol model using analytical and numerical methods were investigated. Threshold effect neuron, when it is exposed to external non-stationary signals that vary in shape, frequency and amplitude was considered.
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Статья научная
This paper highlights the significance of Time-Delay ANN models for predicting shelf life of processed cheese stored at 7-8oC. Bayesian regularization algorithm was selected as training function. Number of neurons in single and multiple hidden layers varied from 1 to 20. The network was trained with up to 100 epochs. Mean square error, root mean square error, coefficient of determination and nash - Sutcliffe coefficient were used for calculating the prediction capability of the developed models. Time-Delay ANN models with multilayer are quite efficient in predicting the shelf life of processed cheese stored at 7-8^oC.
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Статья научная
The notion of rough set captures indiscernibility of elements in a set. But, in many real life situations, an information system establishes the relation between different universes. This gave the extension of rough set on single universal set to rough set on two universal sets. In this paper, we introduce rough equality of sets on two universal sets and rough inclusion of sets employing the notion of the lower and upper approximation. Also, we establish some basic properties that refer to our knowledge about the universes.
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Touch-less Fingerprint Analysis — A Review and Comparison
Статья научная
Touch-less fingerprint recognition system is a reliable alternative to conventional touch-based fingerprint recognition system. Touch-less system is different from conventional system in the sense that they make use of digital camera to acquire the fingerprint image where as conventional system uses live-acquisition techniques. The conventional fingerprint systems are simple but they suffer from various problems such as hygienic, maintenance and latent fingerprints. In this paper we present a review of touch-less fingerprint recognition systems that use digital camera. We present some challenging problems that occur while developing the touch-less system. These problems are low contrast between the ridge and the valley pattern on fingerprint image, non-uniform lighting, motion blurriness and defocus, due to less depth of field of digital camera. The touch-less fingerprint recognition system can be divided into three main modules: preprocessing, feature extraction and matching. Preprocessing is an important step prior to fingerprint feature extraction and matching. In this paper we put our more emphasis on preprocessing so that the drawbacks stated earlier can be removed. Further preprocessing is divided into four parts: first is normalization, second is fingerprint Segmentation, third is fingerprint enhancement and last is the core point detection. Feature extraction can be done by Gabor filter or by minutia extraction and the matching can be done by Support Vector Machine or Principal Component Analysis and three distance method.
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Статья научная
Building a personalized travel recommendation system is important to enhance the satisfaction and experience of travelers. Due to the lack of an efficient online-based tourist assistance system, tourists have faced several challenges in Bangladesh, such as difficulties in planning their trips and making informed decisions. To overcome the existing challenges, in this paper, a prediction model has been developed to predict the suitability of a travel destination based on the user’s preferences and some other relevant factors. Then the system offers personalized recommendations for the best local places to visit, hotels to stay in, transportation services, and travel agencies with the necessary details. This paper utilizes various machine learning classification algorithms to predict the best-suited travel destinations and local tourist spot recommendations for users based on their budget and preferences. The examined results verified that the random forest algorithm provides the best accuracy of 98 percent and is used for tourist place eligibility prediction. The user rating analysis visualized that the proposed mobile application received satisfactory remarks from more than 60 percent of reviewers regarding its effectiveness.
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Towards More Sustainability: A Dynamic Recycling Framework of Discarded Products Based on SD Theory
Статья научная
The mechanism of a recycling system about discarded products is running with a few critical roles and processes. To identify the relationship and collaborate the activities involved in this recycling circle are the very significant work in practice. For the sake the paper explores and identifies the critical drivers underlying the system, based on which a framework is established to explore the relationship among relevant activities consisted of collection, remanufacturing and resale, as well as companies and customers’ behaviours. A dynamic quantitative model is designed to simulate this vigorous relation, which demonstrates and verifies the rule of this relationship with details about the recycling activities. The information will benefit practitioners a lot in terms of the recycling operation planning under different situation.
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