Intersection is an important component of the urban transport network, in where traffic congestion usually takes place. One of the key to solve urban transport problems is to organize the traffic in the intersection r...
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ISBN:
(纸本)9781450363396
Intersection is an important component of the urban transport network, in where traffic congestion usually takes place. One of the key to solve urban transport problems is to organize the traffic in the intersection reasonably and effectively. This paper does research on a specific single intersection, using the video traffic data collection technology, considering signal cycle and phase time which are decided by a real-time traffic flow. The paper developed a self-adaptive timing model on the single target constraint to reduce intersection delay. The model is carried out through fuzzy-genetic algorithm. Matlab simulation analysis and a series of comparison show that the methods of optimization models and geneticalgorithm are effective and feasible.
This paper deals with development of a kinematics model, a trajectory tracking, and a controller of fuzzy-genetics algorithm for 2-DOF Wheeled Mobile Robot (WMR). The global inputs to the WMR are a reference position,...
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ISBN:
(纸本)0819460745
This paper deals with development of a kinematics model, a trajectory tracking, and a controller of fuzzy-genetics algorithm for 2-DOF Wheeled Mobile Robot (WMR). The global inputs to the WMR are a reference position, Pr =(Xr(,)Y(r),theta(r)) and a reference velocity q(r) = (nu(r),pi(r)), which are time variables. The global output of WMR is a current posture P-C = (x(C), y(C) theta(C))(t). The position of WMR is estimated by dead-reckoning algorithm. Dead-reckoning algorithm can determine present position of WMR in real time by adding up the increased position data to the previous one in sampling period. The tracking controller makes position error to be converged 0. In order to reduce position error, a compensation velocities q = (nu, pi)(t) on the track of trajectory is necessary. Therefore, a controller using fuzzy-genetic algorithm is proposed to give velocity compensation in this system. Input variables of two fuzzy logic controllers (FLCs) are position errors in every sampling time. The output values of FLCs are compensation velocities. geneticalgorithms (GAs) are implemented to adjust the output gain of fuzzy logic. The computer simulation is performed to get the result of trajectory tracking and to prove efficiency of proposed controller.
Job shop scheduling problem (JSP) with sequence-dependent setup time and re-entrant work flows is considered in this paper. This is an NP-hard problem which needs to be solved using (meta) heuristic methods (e.g. gene...
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ISBN:
(纸本)9781479912278;9781479912285
Job shop scheduling problem (JSP) with sequence-dependent setup time and re-entrant work flows is considered in this paper. This is an NP-hard problem which needs to be solved using (meta) heuristic methods (e.g. geneticalgorithm (GA)), especially for relatively large instances. However, the GA may face premature convergence (i.e. converging to a local optima), especially for rough solution spaces. In this paper, a fuzzygeneticalgorithm (FGA) is proposed to overcome this issue. The objective is to minimize makespan of such problem. Research results show that the FGA outperforms the standard GA and offers better solutions in the same number of runs.
This paper presents a fuzzygeneticalgorithm approach to generate, assess, and select a System of Systems (SoS) meta-architecture through coupled executable models. A type-1 fuzzy assessor is used to transform crisp ...
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ISBN:
(纸本)9781509006229
This paper presents a fuzzygeneticalgorithm approach to generate, assess, and select a System of Systems (SoS) meta-architecture through coupled executable models. A type-1 fuzzy assessor is used to transform crisp performance attribute inputs into a meta-architecture assessment for use as part of the fitness function of a geneticalgorithm. This algorithm is applied to the generation, assessment, and selection of a meta-architecture for a hypothetical lethal, non-line of sight fires SoS for which the key performance attributes are affordability, flexibility, performance, robustness, and reliability. Combinations of existing systems that have nonlinear interactions are assessed and compared to the United States Military Future Combat System. Results show that this approach produces architectures that provide the same performance without requiring the purchase of any new systems, potentially saving billions of dollars.
In recent years, the usage of social media has been increasing exponentially because of its various real world applications in digital communication such as content sharing, entertainment, creating awareness, sending ...
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In recent years, the usage of social media has been increasing exponentially because of its various real world applications in digital communication such as content sharing, entertainment, creating awareness, sending alerts, etc. One such task is to upload images/videos, write comments and post user reactions to express feedback, which can then be used to study human personality traits. Classifying images according to different personality traits, like Agreeableness, Conscientiousness, Extraversion, Neuroticism, Openness, etc., is challenging and essential because of several real-world applications mentioned above. This paper proposes a new personality-traits based method for classifying social images using fuzzy and geneticalgorithms. For each user, the proposed approach extracts profile picture, banners and descriptions to construct a set of vocabularies with the help of text detection, recognition and image annotation. For each word in the vocabulary, we employ a fuzzy logic-based method for obtaining a fuzzy co-occurrence matrix by defining the relationship between the words, which results in a fuzzy co-occurrence matrix for each input data point. We also propose a geneticalgorithm based fusion method to generate a feature matrix, which is ultimately fed to the fully connected neural network for classification. The effectiveness of the proposed approach is demonstrated on our dataset with five classes containing 5000 images along with four benchmark datasets, namely, (i) five classes of Liu et al.'s dataset (33556 images) (ii) five classes of PERS dataset (28434 images), (iii) ten classes of Krishnani et al.'s dataset (2000 images), and (iv) two classes of facial emotions of FERPlus dataset (26398 images). The results show that the proposed approach outperforms the existing methods for all the datasets in terms of classification rate. (c) 2021 Elsevier B.V. All rights reserved.
Ships are complex structures composed of various components with exclusive dynamic behaviors and natural frequencies, so assessing their vibration behavior is essential. Some situations in practical applications could...
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Ships are complex structures composed of various components with exclusive dynamic behaviors and natural frequencies, so assessing their vibration behavior is essential. Some situations in practical applications could alter the ship's dynamic characteristics and cause significant changes in its vibration behavior. Since the ship's mass is one of the most important dynamic parameters in determining vibration behavior, local mass change can lead to changes in its dynamic characteristics and must be considered. This study aims to develop a method to predict the effect of the location and magnitude of mass change on the ship hull's vibration behavior. It would be feasible to enhance the dynamic behavior and reduce undesirable noises by locating the mass change on the ship hull. In this regard, experimental and numerical modal analysis is performed on a scaled model of a naval ship hull. The baseline FE model is used to calculate the variation in frequencies of the model caused by different local mass change scenarios. Using these measurements a fuzzy system is generated and optimized by genetic and Particle Swarm Optimization algorithms. Finally, the efficiency of the fuzzy-PSO is validated by different mass change scenarios foreseen on the physical model of the ship hull.
The aim of this paper is to create a model for mapping the surface electromyogram (EMG) signals to the force that generated by human arm muscles. Because the parameters of each person's muscle are individual, the ...
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The aim of this paper is to create a model for mapping the surface electromyogram (EMG) signals to the force that generated by human arm muscles. Because the parameters of each person's muscle are individual, the model of the muscle must have two characteristics: (1) The model must be adjustable for each subject. (2) The relationship between the input and output of model must be affected by the force-length and the force-velocity behaviors are proven through Hill's experiments. Hill's model is a kinematic mechanistic model with three elements, i.e. one contractile component and two nonlinear spring elements. In this research, fuzzy systems are applied to improve the muscle model. The advantages of using fuzzy system are as follows: they are robust to noise, they prove an adjustable nonlinear mapping, and are able to model the uncertainties of the muscle. Three fuzzy coefficients have been added to the relationships of force-length (active and passive) and force-velocity existing in Hill's model. Then, a geneticalgorithm (GA) has been used as a biological search method that can adjust the parameters of the model in order to achieve the optimal possible fit. Finally, the accuracy of the fuzzygenetic implementation Hill-based muscle model (FGIHM) is invested as following: the FGIHM results have 12.4% RMS error (in worse case) in comparison to the experimental data recorded from three healthy male subjects. Moreover, the FGIHM active force-length relationship which is the key characteristics of muscles has been compared to virtual muscle (VM) and Zajac muscle model. The sensitivity of the FGIHM has been evaluated by adding a white noise with zero mean to the input and FGIHM has proved to have lower sensitivity to input noise than the traditional Hill's muscle model. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
In order to meet the demands of dynamic path optimization for road-network real-time traffic information, the model of dynamic transportation network based on the fuzzy-genetic algorithm were constructed in this paper...
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ISBN:
(纸本)9781479958252
In order to meet the demands of dynamic path optimization for road-network real-time traffic information, the model of dynamic transportation network based on the fuzzy-genetic algorithm were constructed in this paper. Firstly, through the two-dimensional fuzzy design in the fuzzy logic toolbox of Matlab software, the real-time traffic flow parameters were transformed into crowdedness degree in the range of 0 to 1. Next, the dynamic network model was established by using graph theory. At last, the short circuit of driving scheme is generated after optimizing the dynamic network model using geneticalgorithm. Taking the road information in Taiyuan as an example, the results show that the improved algorithm has the characteristics of good real time, dynamic and stability.
Smart farming has played a significant role in decision support system to maximize the yield with minimum consumption of water in the field of agriculture. The main objective of this paper is to design and develop an ...
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Smart farming has played a significant role in decision support system to maximize the yield with minimum consumption of water in the field of agriculture. The main objective of this paper is to design and develop an innovative multilevel model ensembling for accurate estimation of crop coefficient (K-c) and reference evapotranspiration (ETc) using fuzzy-genetic (FG) and Regularization Random Forest(RRF) models. This study present the water requirement of three crops namely (maize, wheat(1) and wheat(2)) in which ET(c )is a function of the product of the crop coefficient K-c and reference evapotranspiration (ET0). The proposed model is used to analyze the data collected by IMD, Pune and PAU, Ludhiana (case study) for decision making in a crop water model. The proposed FG-RRF(ETc) crop prediction model efficiently estimated K-c and ETc and make an efficient decision.
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