Journal of Intelligent & Fuzzy Systems - Volume 31, issue 4

Authors: Rocha, Álvaro

Article Type: Editorial

DOI: 10.3233/JIFS-169085

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2059-2059, 2016

Authors: Lino, Adriano | Rocha, Álvaro | Sizo, Amanda

Article Type: Research Article

Abstract: Empirically, symbolic regression tries to identify, through genetic programming and within the sphere of mathematical expressions, a model which best explains the relationship between variables in a given set of data, in terms of precision and simplicity. Virtual teaching and learning environments focused on evaluation have been previously investigated, as they offer teachers an effective teaching and learning tool and the student the possibility of computer-assisted evaluation and customized learning. Within this context, the present paper introduces an alternative approach to automatic evaluation in virtual teaching and learning environments, which offers the following improvements when compared to other methods: a) …superior accuracy when compared with the linear regression method; b) simplicity of implementation; c) possible deduction of final student grades; and d) context adaptive. To this extent, a case study was applied to the LabSQL environment, with the purpose of clarifying the benefits of symbolic regression via genetic programming, while emphasizing its efficiency and simplicity of implementation. Show more

Keywords: Symbolic regression, genetic programming, virtual teaching and learning environments, automatic evaluation, SQL

DOI: 10.3233/JIFS-169045

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2061-2072, 2016

Authors: Dimitrijević, Dejan | Obradović, Đorđe | Nedić, Nemanja | Luković, Ivan

Article Type: Research Article

Abstract: The paper presents a noninvasive scoliosis and other spine disorder automatic diagnostic solution implemented using low-cost commodity sensors, but still achieving adequate precision. The cost of similar commercial solutions is prohibitive to have them acquired by many healthcare institutions in less-developed countries, thus we have developed a low-cost one. The proposed solution can easily be used by healthcare institutions with small investment for obtaining otherwise expensive equipment. The precision and usefulness of designed spine disorder diagnostic solution is thoroughly tested during students’ annual health checkups.

Keywords: Scoliosis screening, low-cost commodity sensors, POTSI, DAPI, spine disorder

DOI: 10.3233/JIFS-169046

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2073-2082, 2016

Authors: Kang, Z.L. | Xu, L.J. | Li, Y. | Huang, P.

Article Type: Research Article

Abstract: This study designs an intelligent soilless culture device that overcomes the disadvantages of the traditional soilless culture device, such as complex structure, low automation, and management inconvenience. The said device has an embedded controller S3C6410 as its core and realizes the intelligent supplemental lighting of the soilless culture device. It is also capable of the automatic heating, automatic circulation, and automatic ion concentration balance of the nutrient solution by detecting the illumination, ion concentration of the nutrient solution, temperature, and other parameters through sensors. The soilless culture device also communicates with a mobile phone in real time through the CDMA …module. The users can query various parameters of the device any time and send the control command in real time through the mobile phone. After testing, the device not only realizes on-demand and subband intelligent supplemental lighting and the automatic concentration balance, automatic heating, and automatic circulation of the nutrient solution, but also achieves remote wireless monitoring through the mobile phone. The culture contrast experiment of the leaf lettuce shows that the device developed in this study is superior to other traditional soilless cultivation devices. It has the significant characteristics of strong practicability, good scalability, stable and reliable work, and intuitive and simple manipulation. Show more

Keywords: Soilless culture, intelligent supplemental lighting, automatic balance, remote wireless monitoring, embedded controller

DOI: 10.3233/JIFS-169047

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2083-2089, 2016

Authors: Cai, Ken

Article Type: Research Article

Abstract: The near-infrared (NIR) camera is extensively used in the optical tracking system for surgical navigation because it can effectively restrain the interference from environmental light in the imaging process. The accuracy of the optical tracking system is determined by camera calibration. However, the existing calibration methods are intended for visible-light cameras and are inapplicable to NIR cameras because the latter has no capacity to capture the calibration pattern. In the study a calibration pattern composed of near-infrared surface-mounted diodes is designed, and the corresponding intelligent algorithm based on geometric information that can be used to calibrate the NIR camera is …proposed. Using this method requires the implementation of automatic decision of angular points via triangular gridding. The experimental results show that our proposed method is accurate and effective in meeting the application requirements of surgical navigation. Show more

Keywords: Calibration temthe systeplate, intelligent calibration, near-infrared camera, surgical navigation system

DOI: 10.3233/JIFS-169048

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2091-2100, 2016

Authors: Li, Ming | Ma, Honglu | Gu, Baijie

Article Type: Research Article

Abstract: The typical teaching–learning-based optimization (TLBO) algorithm tends to devolve into local optimization and suffers from the rapid loss of population diversity. In this study, an improved TLBO algorithm with group learning (GTLBO) is established to solve these problems. In the proposed algorithm, a class is divided into several groups. The individual with the highest level is selected as the teacher for each group. Then, the teacher implements the TLBO algorithm in each group. This strategy of group learning can maximize the time before the students reach the teacher’s level and effectively ensure population diversity. Given an effectively diverse population, the …idea of reversing the beginning and ending is introduced to boost the convergence rate of the algorithm. Moreover, a matrix displacement method is provided to solve the premature termination phenomenon of the algorithm. Finally, the performance of the GTLBO is investigated across six complex high-dimensional benchmark functions. Results obtained through experiments show that the GTLBO conduces enhanced performance in solving problems of multimodal function optimization. The convergence speeds and solution accuracy of the proposed algorithm are significantly improved compared with those of the typical TLBO algorithm. Show more

Keywords: Teaching–learning-based optimization, group learning, complex high-dimensional optimization problem

DOI: 10.3233/JIFS-169049

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2101-2108, 2016

Authors: Xu, L.J. | Kang, Z.L. | Huang, P. | Luo, H.

Article Type: Research Article

Abstract: The intelligent identification and positioning for melons and other fruits are important links for the melon and fruit picking robot to naturalize smooth picking, thus directly affecting the picking efficiency and success rate. Considering that the picking robot has low identification rate and low positioning accuracy for melons and fruits, this paper designed an intelligent watermelon identification and positioning method in a natural scene. This method included the following steps: first, the natural watermelon images shot by the left and right cameras were captured to increase the proportion of the watermelon region in the image; second, erosion, adaptive noise cancellation …and filling, as well as other techniques were used for the captured watermelon image to identify the watermelon region and calculate its values of barycentric coordinates; third, the squint binocular positioning algorithm was designed based on the values of watermelon barycentric coordinates in two images to obtain the actual watermelon three-dimensional space coordinates, using the left camera as the origin of coordinates. The experiment verified that the relative positioning errors of this method were within±15% for the watermelon three-dimensional space coordinates in a natural scene, thereby providing a key intelligent identification and positioning method for the watermelon picking robot. Show more

Keywords: Machine vision, intelligent identification and positioning, squint binocular positioning, natural watermelon image

DOI: 10.3233/JIFS-169050

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2109-2117, 2016

Authors: Huang, Haoran | Cai, Ken

Article Type: Research Article

Abstract: This paper applies the error-eliminating theory to create a new method for fuzzy multiple attribute decision-making problems whose attribute values contain interval numbers, triangular fuzzy numbers, and trapezoidal fuzzy numbers. First, the concepts of error, loss, and extreme loss are discussed in the context of fuzzy multiple attribute decision-making problems combined with error-eliminating theory. Second, the error function is constructed, and the extreme loss value is calculated based on decision makers’ psychological threshold interval and error types. Third, the attribute loss value is calculated through error values and extreme loss values based on the decision makers’ psychological characteristics of loss …aversion. And then, the overall loss value of alternatives is obtained by the attribute loss value. Finally, the ranking and selection of alternatives are conducted based on the overall loss value. Using the practical example of the location of agricultural products’ logistics center, the rationality and scientificity of this study are illustrated by comparing the decision-making method proposed in this paper with three other methods. Show more

Keywords: Fuzzy multiple attribute decision making, error, loss, psychological threshold, error-eliminating theory

DOI: 10.3233/JIFS-169051

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2119-2127, 2016

Authors: Yue, Hongwei | Cai, Ken | Lin, Hanhui | Chen, Huazhou | Zeng, Zhaofeng

Article Type: Research Article

Abstract: Diagnosis of rice planthopper pests based on imaging technology is an efficient means to develop intelligent agriculture. Effective contour automation extraction is an important pretreatment technology at the early stage for identifying and classifying rice planthoppers. The traditional graph cut method-based active contour (GCBAC) requires human–computer interaction during segmentation. In addition, GCBAC is prone to shrinking bias phenomenon, thereby providing short-boundary segmentation results. This study proposed a novel approach to overcome these two problems. First, rice planthopper initial segmentation was completed through discrete cosine transform to weaken the interference of background, and this segmentation was used as the initial contour …of GCBAC to avoid artificial contour initialization. Then, dilation direction of contour line on both sides was changed to a one-way lateral dilation to avoid boundary shrinking bias. Results show that the proposed method can accurately locate pest region and clearly segment the contour of rice planthoppers. Show more

Keywords: Rice planthopper, contour extraction, graph cut, GCBAC algorithm

DOI: 10.3233/JIFS-169052

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2129-2135, 2016

Authors: Bo, Li | Luo, Xuegang | Wang, Huajun

Article Type: Research Article

Abstract: To solve the shortcomings of traditional guided image filtering (GIF) in edge preservation and denoising performance, this study describes a novel generalized guided image filtering method, which integrates an artificial swarm optimization algorithm. A locally adaptive weighting based on monogenic phase congruency and chaotic swarm optimization is used to produce a more robust method. Since the fixed regularization parameter cannot adapt to the grayscale difference between flat and edge patches, the box filter radius and regularization parameter of guided image filtering have significant influences on image-denoising effects. The chaotic swarm optimization algorithm, which is an improved optimization algorithm with a …self-adapting search space, is adopted to find their optimal values for the best denoising effects. Compared with traditional guided image filtering for image denoising and other state-of-the-art methods with image quality as a performance metric, experimental results showed that the proposed denoising algorithm can not only remove noise efficiently and reduce halo artifacts, but can also preserve the edge texture well. Show more

Keywords: Image denoising, adaptive weighted guided image filter, artificial swarm optimization, parameter selection

DOI: 10.3233/JIFS-169053

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 4, pp. 2137-2146, 2016