The generation of fuzzy rules from samples is significant for fuzzy modelling. To improve the robustness of Wang-Mendel (WM) method, an improved WM method to extract fuzzy rules from all the regularized sample data wa...
详细信息
To recover QAM signals at the receiver of blind equalizer, a fuzzyc-meansclustering Neural Network Blind Equalization algorithm based on Signal Transformation (ST-FNN-BEA) is proposed. The proposed algorithm uses si...
详细信息
ISBN:
(纸本)9783037850046
To recover QAM signals at the receiver of blind equalizer, a fuzzyc-meansclustering Neural Network Blind Equalization algorithm based on Signal Transformation (ST-FNN-BEA) is proposed. The proposed algorithm uses signal transformation method to debase the computational complexity of equalizer input signals and speed up the convergence rate, and makes use of fuzzy c-means clustering algorithm dividing the equalizer input signals into each cluster center with different membership values to improve the equalization performance. The proposed ST-FNN-BEA outperforms Neural Network Blind Equalization algorithm (NN-BEA) and Neural Network Blind Equalization algorithm based on Signal Transformation (ST-NN-BEA) in improving convergence rates and reducing mean square error. The performance of ST-FNN-BEA is proved by the computer simulation with underwater acousticchannels.
Pearl's color is an important feature to assess its value, including the hue and its color depth. A method for pearl color classification was investigated in this paper computer Vision is used to process the pearl...
详细信息
ISBN:
(纸本)9780769538921
Pearl's color is an important feature to assess its value, including the hue and its color depth. A method for pearl color classification was investigated in this paper computer Vision is used to process the pearl image after transforming it from RGB to HSV color model, which can show the hue and color depth information of pearl. According to the histogram of V (Value) weight, the bright area is extracted by Ostu Segmentation and the average value of H (Hue) and S (saturation) are obtained Aiming at the standards of hue classification, the artificial neural network method based on RPROP algorithm is adopted;Aiming at the color depth's difference, fuzzy c-means clustering algorithm is adopted to class' the average value of S. The proposed method can be used for the first classification according to the surface color of pearl and further classification according to the saturation of pearl in the same color series and realizing the standard classification of pearl quality.
This paper considers the problem of joint spectrum sensing and secondary data transmission in the relay-assisted cognitive radio networks. An optimization problem is formulated that searches for the cluster-wise relay...
详细信息
ISBN:
(纸本)9781538623480;9781538623473
This paper considers the problem of joint spectrum sensing and secondary data transmission in the relay-assisted cognitive radio networks. An optimization problem is formulated that searches for the cluster-wise relay selection and consequent power allocation with an objective to maximize the sum throughput of the secondary network under the constraints of the interference power limit and the probability of primary user's (PU) signal detection. fuzzy c-means clustering algorithm is applied to associate a set of secondary users (SUs) to form a cluster at the source as well as in destination end followed by their link establishment via a particular relay. closed form expression for the optimal cluster power allocation is derived and the performance of the proposed system is investigated in terms of secondary network throughput and sum cluster power for SU data transmission. A large set of simulation results show that a gain similar to 24.37% and similar to 36.03% in SU throughput are achieved for the proposed scheme when compared to the existing works.
Due to the increasing deployment of Internet of Things in the mining industry, portable gas monitoring devices have been widely used. According to the character of time series of gas stream, the paper studies on mathe...
详细信息
ISBN:
(纸本)9781728135557
Due to the increasing deployment of Internet of Things in the mining industry, portable gas monitoring devices have been widely used. According to the character of time series of gas stream, the paper studies on mathematics analysis method of time series similarity based on pattern beam and pattern set. combining with short-time stationary of gas data, the feature selection method of short-time gas data based on sliding time window is proposed. On the basis of the fuzzy c-means clustering algorithm, short-time gas stream in the fuzzy c-means clustering algorithm is put forward to analyze the convergence effects of the data of gas stream based on binary statistic and multivariate statistic, which provides qualified data that available for analysis and calculation for data correction of gas sensors afterward.
Life of modern people becomes more convenient and rich in material side but worse in mental side due to life stress. This results in bloom of some diseases such as insomnia. Listening to musiccould be one way to make...
详细信息
ISBN:
(纸本)9781614994404;9781614994398
Life of modern people becomes more convenient and rich in material side but worse in mental side due to life stress. This results in bloom of some diseases such as insomnia. Listening to musiccould be one way to make people feel smooth. Some previous literature had advocated the efficiency of music therapy, however, only a few previous studies discussed and connected personal cognition (subjective indicators) with music features (objective indicators). Therefore, the aim of the study is to investigate what kind of musiccharacteristics can spiritually relax people and obtain the therapeutic music from above results. Firstly, this study collected 25 different styles of music as samples. These songs were classified with fuzzy c-means clustering algorithm. According to our experimental result, music with mild amplitude, slow speed, and positive feelings can enable soothing in mind. The findings would also fit in with physiological signals (Heart Rate Variability) to ensure the consistency in psychology and physiology. This finding can provide suggestions on selection of therapeutic music. In addition, musicians can compose appropriate therapeutic music for patients of different mental illness.
Adaptive E-learning platforms provide personalized learning process relying mainly on learning styles. The traditional approach to find learning styles depends on asking learners to self-evaluate their own attitudes a...
详细信息
Adaptive E-learning platforms provide personalized learning process relying mainly on learning styles. The traditional approach to find learning styles depends on asking learners to self-evaluate their own attitudes and behaviors through surveys and questionnaires. This approach presents several weaknesses including the lack of self-awareness of learners of their own preferences. Furthermore, the vast majority of learners experience boredom when they are asked to fill out the corresponding questionnaire. Besides that, traditional approach assumes that learning styles are fixed, and cannot change over time. In this paper, we propose a generic approach for detecting learning styles automatically according to a given learning styles model. In fact, our approach does not depend on a specific LSM. This work consists of two major steps. First, we extract learning sequences from learners log files using web usage mining techniques. Second, we classify the extracted learners' sequences according to a specific learning style model using clusteringalgorithms. To perform our approach we use Felder-Silverman Model as LSM and fuzzyc-means as a clusteringalgorithm. We have conducted an experimental study using a real-world dataset. The obtained results show that our approach outperforms traditional approach and provides promising results.
In this paper, it is shown that accurate load forecasts are vital for short, medium and long-term operations. The energy load forecast has its impact on different outcomes and decisions for power generation companies....
详细信息
ISBN:
(纸本)9781450363921
In this paper, it is shown that accurate load forecasts are vital for short, medium and long-term operations. The energy load forecast has its impact on different outcomes and decisions for power generation companies. It also has its influence on electricity market prices. The purpose of this research is to develop an energy load forecasting model to predict future electricity loads for energy load management. The forecasting model is based on a straightforward sequential methodology by implementing subtractive clusteringalgorithm, fuzzy c-means clustering algorithm and eventually an adaptive Neuro-fuzzy inference system architecture for generating the best fuzzy inference system using historical energy load data. In addition, the influence of different weather factors on energy loads such as dry-bulb temperature is counted in.
Virtual learning community is a kind of learning environment based on network is a new type of learning organization. However, Virtual Learning community in the teaching data is often messy, fragmentary, it's valu...
详细信息
ISBN:
(纸本)9781509015856
Virtual learning community is a kind of learning environment based on network is a new type of learning organization. However, Virtual Learning community in the teaching data is often messy, fragmentary, it's value is often difficult to be detected and reasonable to use data mining techniques to deal with data will give us a analysis to study the effect of get twice the result with half the effort. Personalized teaching has always been a difficult point in the network teaching research, and the extraction and analysis of the characteristics of the learner's learning is the basis of personalized teaching. The purpose of this paper is through the acquisition learning in virtual learning community of learning behavior record and analysis learners learning characteristics, through the establishment of learning feature vectors, using fuzzyc-meansalgorithm for mining learners common characteristics. The common characteristics of individual learners as a research object of the transformation to the learner that clusteringcenter feature vector as the research object, so that learning features simplified. characteristics similar to the learner to divide into a group, formulated by the relevant experts in the field of practical teaching strategies and learning tasks, for each group are for teaching, personalized teaching, so as to improve the learning efficiency. Development of individualized instruction.
The present study reports an investigation on identification of priority areas of improvement for small passenger car segment in the Indian market. A total of 750 responses on importance and satisfaction rating of 16 ...
详细信息
The present study reports an investigation on identification of priority areas of improvement for small passenger car segment in the Indian market. A total of 750 responses on importance and satisfaction rating of 16 attributes in a 7-point Likert-type ordinal rating scale were collected from small car owners in Delhi using a paper and pencil instrument. Revised importance-performance analysis with fuzzy c-means clustering algorithm was used to identify the priority areas of improvement in small passenger cars. The analysis technique effectively identified the factor structure of consumer satisfaction and derived various management schemes for small passenger cars by analysing consumers' importance and satisfaction data. The priority areas of improvement were obtained by comparing the factor structure with the management scheme. The results indicate that safety, security and advanced vehicle technology options are the priority areas of improvement for small passenger cars. The study identified that the consumers are satisfied with the performance of purchase price, driving range, annual fuel cost, annual maintenance cost, top speed, seating comfort, appearance/style, emission, acceleration time and resale value in small cars, indicating the need to retain these attributes at their present levels to maintain competitive advantage. The engine power is identified under 'possible overkill', which indicates an opportunity for automobile manufacturers to possibly reduce the engine power to save some resources and reallocate the same for improvement of priority attributes. The findings of the present study provide valuable insight into the product specifications that the automobile manufacturers should focus on, to make new-generation small cars more attractive to Indian consumers.
暂无评论