Journal of Intelligent & Fuzzy Systems - Volume 37, issue 4

Authors: Ji, Jiang-Tao | Yang, Lin-Hui | Jin, Xin | Ma, Hao | Pang, Jing | Huang, Rong-Biao | Du, Meng-Meng

Article Type: Research Article

Abstract: Pot seedling transplanting is the main way of vegetable planting, there were some problems of labor intensity and low level of automation in the process of mechanized transplanting of vegetable pot seedling. Aiming at this problem, this paper designed an intelligent transplanting system for vegetable pot seedling, which included the function of the seeding storage mechanism, the seedling feeding mechanism, the ejecting seedling mechanism, the pinch mechanism and the planting mechanism, the system monitors the whole movement process of planting through pressure sensing, stroke detection and limit switch, obtains each planting stage of the seedlings during planting, and uses the …CCD camera to identify the key steps of planting and seedlings to determine whether it is missing. Three broccoli seedlings with different moisture content and the age of 42d were used as the experimental object of seedlings planting experiment. Results indicated that: Under the conditions of meeting the agronomic requirements of vegetable pot seedlings, when the speed of picking-up seedlings was 75 seedlings per minute, which resulted in a 95% success rate of picking-up seedlings and 5% leaked seedlings rate, the planting effect of vegetable pot seedlings was the best. The research can provide useful reference for the development of intelligent transplanting technology of vegetable pot seedling. Show more

Keywords: Vegetable pot seedling, intelligent transplanting system, PLC control, design

DOI: 10.3233/JIFS-179322

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4847-4857, 2019

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4859-4859, 2019

Authors: Wang, Haofang | Yun, Ruan | Zhao, Ranhang | Qi, Zhen

Article Type: Research Article

Abstract: Flash flood is one of the most significant natural disasters in China, particularly in mountainous area, causing heavy economic damage and casualties of life. For numerous small hilly basins that need flash flood prevention and control with limited funds, it is necessary to give a priority order or to determine which basin needs to be harnessed firstly. Flash flood risk assessment is critical to an efficient flash flood management. Among many flash flood risk evaluation methods in literatures, variable fuzzy method (VFM) was chosen in this paper. To verify the results of VFM, fuzzy clustering analysis (FCA) is also used. …First, taking Licheng county with 119 small basins in China as an example, 9 indexes were identified among index system, based on disaster-breeding environment (or underlying surface conditions) of small basin in hilly region. Risk levels are divided into three grading levels such as high, medium and low. Second, VFM was introduced, and the flash flood risk grade eigenvalue (H) of each small basin was calculated. The results show that no small basin belongs to high risk level, 14 basins belong to low risk level, and the remaining 105 small basins belong to medium risk level. Third, FCA was used to verify the result of VFM. The results of two methods show that they are nearly in consistence. This paper shows that VFM is feasible for flash flood risk evaluation. Finally, the priorities for flash flood mitigation of 119 small watersheds in Licheng county are mapped out, which will provide effective help for flood disaster mitigation of small basin. Show more

Keywords: Variable fuzzy method, fuzzy clustering analysis, flash flood risk, disaster-breeding environment, small basin

DOI: 10.3233/JIFS-171089

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4861-4872, 2019

Authors: Khan, Asghar | Hadi, Asmat | Ibrar, Muhammad | Jun, Y.B.

Article Type: Research Article

Abstract: Using the notions of a soft set and a fuzzy set, Jun’s introduced a new type of notion called a hybrid structure, which is a generalization of soft set and fuzzy set. In this paper, we apply hybrid structure in hemirings and introduce the concept of hybrid h -ideals of hemirings and the related properties are investigated. Some operational properties of hybrid structures are first investigated. The concepts of a hybrid h -sum and a hybrid h -product are discussed and the related properties are investigated. The notions of hybrid h -ideals, hybrid h -bi-ideals and hybrid h -quasi-ideals are …introduced and several properties are provided. The notion of a hybrid level set is introduced and the basic properties of hybrid h -ideals, hybrid h -bi-ideals and hybrid h -quasi-ideals are studied in detail. The characterizations of h -hemiregular hemirings are discussed and several important results of a h -hemiregular hemirings are provided. Show more

Keywords: Hybrid structure, hybrid structures operations, hybrid h-sum, hybrid h-product, hybrid h-ideals, hybrid h-bi (h-quasi)-ideals, h-Hemiregular hemirings.

DOI: 10.3233/JIFS-171587

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4873-4889, 2019

Authors: Zhou, Yimin | Li, Zhifei

Article Type: Research Article

Abstract: This paper proposes a novel image processing method to extract the gender feature from frontal face combining Principal Component Analysis (PCA) and an improved Genetic Algorithm (GA) to reduce the interference of facial expression, lighting or wear. The collected facial images are first cropped and aligned automatically, then the gray-level information can be converted to feature vectors via PCA. After eigen-features are extracted with high classification performance by the aid of an improved GA, the neural network classifier can be trained accordingly. Compared to the classification methods based on global gray-level information, the obtained classifier has better identification rate but …less used feature dimension, so the calculation load can substantially be reduced during training and classification procedures, which benefits to the development of a real-time identification system. Furthermore, FERET dataset and FEI dataset are used to validate the generality of the proposed method, where 94% and 96% accuracy rates of the gender recognition can be achieved respectively. Show more

Keywords: Gender recognition, Genetic feature selection, Neural network, Principal component analysis, Frontal face

DOI: 10.3233/JIFS-17193

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4891-4902, 2019

Authors: Samadi, Aliasghar | Jazaeri, Mostafa

Article Type: Research Article

Abstract:  An isolated network with Wind Turbine implemented by Double Fed Induction Generator (WTDFIG) that maintaining different electrical variables in safe ranges following a severe transient condition is always a serious challenge. This paper proposes a control scheme based on Auto-Tuning Fuzzy PI (ATFPI) concept for the Rotor Side Converter (RSC) of the DFIG by online tuning of the output scaling factor of the ATFPI for enhancement the transient behavior of the system under various condition of operation. The scheme includes a coordinator unit which is elaborated to effectively regulate the frequency and active power of the system. The performance of …the proposed ATFPI controller is evaluated in a typical network in Matlab Simulink environment. Obtained results show that the control can successfully meet all functions drawn in the scope and easily put behind the conventional competitors like conventional PI and/or fuzzy PI controllers. Show more

Keywords: DFIG, PI controller, fuzzy PI controller, modal analysis, transient condition, rotor side convertor

DOI: 10.3233/JIFS-171953

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4903-4921, 2019

Authors: Agarwal, Shikha | Dhyani, Akshay | Ranjan, Prabhat

Article Type: Research Article

Abstract: High dimensional data have brobdingnagian number of features, but not all features are useful. Irrelevant and redundant features may even reduce the classification accuracy. Feature selection is a process of selecting a subset of relevant features to decrease the dimensionality of data. When applied on high dimensional datasets (Big Data) the feature selection methods perceives many challenges and it is pertinent to come up with the new methods or revamp the existing methods. In this study, a new method ‘Newtonian particle swarm optimization (NPSO)’ has been proposed. In the proposed method Newton’s second law of motion has been used to …update the learning mechanism of PSO. In NPSO, particle not only learn from the position but also from the mass and acceleration of neighboring particles. The proposed method is mathematically validated at equilibrium using eigen values. Further, the proposed method has been applied on high dimensional microarray gene expression dataset. The NPSO is also compared with other state of art feature selection methods. Selected features, classification accuracy and dimension reduction are used to appraise the goodness of the proposed method. Mathematical validation and experimental results clearly validates the merits of the proposed method in field of feature selection. This paper show the classwise analysis of SRBCT, Brain1, 11-Tumor and 14-Tumor datasets. When number of classes increased dimension reduction is increased but classification accuracy of dataset is decreased. Show more

Keywords: Particle swarm optimization, law of motion, big data, microarray gene expression, cancer data, feature selection, classification accuracy

DOI: 10.3233/JIFS-181177

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4923-4935, 2019

Authors: Gałka, Jakub | Jaciów, Paweł

Article Type: Research Article

Abstract: In this paper, we propose a new method for concurrent accuracy and computational efficiency optimization using a fuzzy clusters tree for i-vector speaker identification. The design assumptions and an algorithm for a new type of fuzzy i-vector tree construction were introduced. The obtained solution was evaluated using the NIST 2014 i-Vector Speaker Recognition Machine Learning Challenge dataset. A 15% relative equal error rate reduction for a 74% reduction in computation time was achieved when compared to the baseline with only a 5.5% relative identification rate loss for discussed tree configurations.

Keywords: speaker recognition, fast identification, i-vector, fuzzy clustering, decision trees

DOI: 10.3233/JIFS-181359

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4937-4949, 2019

Authors: Bernardes, Nemerson D. | Castro, Felipe A. | Cuadros, Marco A.S.L. | Salarolli, Pablo F. | Almeida, Gustavo M. | Munaro, Celso J.

Article Type: Research Article

Abstract: The use of the fractional PID controller or simply PIλ Dμ has brought the addition of two new parameters, λ and μ . Although this results in a greater flexibility, they make the tuning of the controller more complex and slower. One solution to this is the use of fuzzy logic to perform a self-tuning of the parameters. Through its rules of inference, the algorithm can determine a better tuning in real time. This article presents a practical application of a PIλ self-tuned with the use of fuzzy logic, in a differential mobile robot. …Three different types of speed controllers are presented. A lemniscate curve is used for the robot’s trajectory tracking, with and without disturbance in the speed control of the wheels. Dynamic selection of better controller parameters is obtained by the fuzzy controller and applied on the speed control of the wheels of a mobile robot. A camera is used as feedback for the tracking controller, so the real pose estimated is acquired through image processing. The self-tuning controllers are evaluated, compared to a fixed-tuning controller, with its parameters being acquired through traditional, well consolidated methods. The implementation, practical results and conclusions are hereby presented. Show more

Keywords: Backstepping control, fuzzy logic, PID controller, fractional control

DOI: 10.3233/JIFS-181431

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4951-4964, 2019

Authors: Solat, Alireza | Ranjbar, Ali Mohammad | Mozafari, Babak

Article Type: Research Article

Abstract: Doubly-fed induction generator (DFIG) is the most commonly used technology for wind power generation due to the variable speed performance, decoupled control of active and reactive powers, and high efficiency. However, the DFIG originally cannot participate in damping of power system oscillations since it is not synchronously connected to the power system. This paper proposes an optimal and robust additional damping controller for the DFIG wind turbine to contribute it to damp power system oscillations. It is a fuzzy logic controller that its parameters are optimally tuned using the genetic algorithm (GA). The proposed controller modifies the DFIG active power …output by using feedback from grid oscillations. Here, a comparative study is carried out for different feedback signals to determine the best of them. Comparing the results reveal that the rotor speed difference of synchronous generators is the best feedback signal to damp power system oscillations. Time domain simulations also confirm the effectiveness and robustness of the proposed controller under both the small and large disturbances. Show more

Keywords: Fuzzy logic, damping controller, doubly-fed induction generator, power system oscillations

DOI: 10.3233/JIFS-181524

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4965-4978, 2019