In this paper, least squares support vector machine (LS-SVM) based motion control of a mobile robot in dynamic environment is proposed under the measured data with uncertainties. The proposed scheme can control the robot by consideration of local minima, where the controller is based on Lyapunov function candidate and considers virtual forces information. Comparing with standard support vector ...

Steinwart was the first to prove universal consistency of support vector machine classification. His proof analyzed the ‘standard’ support vector machine classifier, which is restricted to binary classification problems. In contrast, recent analysis has resulted in the common belief that several extensions of SVM classification to more than two classes are inconsistent. Countering this belief, ...

intrusion detection system (IDS) is a device or software application that Li et al (2) proposed a fuzzy multi-class support vector machine algorithm, denoted. Detection System. Multiclass SVM, Neural Network, Support Vector Machine. network and (2) network based intrusion detection system which analyzes. of network intrusion detection systems for struggling progressively leading state-of-the ar...

forecasting of municipal waste generation is a critical challenge for decision making and planning,because proper planning and operation of a solid waste management system is intensively affected by municipal solid waste (msw) streams analysis and accurate predictions of solid waste quantities generated. due to dynamic and complexity of solid waste management system, models by artificial intell...

In this paper, a denoising algorithm and simulation experiments of algorithm based on wavelet transform and support vector machine (SVM) image is proposed, a new method is adopted in the selection of characteristic vector of support vector machine, based on training of support vector machine, the support vector machine model is used to distinguish between noise and the original image, to achiev...

Breast cancer is the most common cancer in women, and is considered one of the most common causes of death. It increases by an alarming rate globally. Earlier detection and diagnosis could save lives and improve quality of life. In this paper, a new method for breast cancer diagnosis is presented. The proposed method, SVM-Kmeans, combines Kmeans, an unsupervised learning clustering technique, w...

Abstract This paper studies on methods taken in solving the existing network disorders in network intrusion detection. Traditional parameter-optimized Support Vector Machine (SVM) may easily generate improper parameter-selections, and may further lead to a low accuracy in network intrusion detection. In order to overcome such problems, so well as to ensure the network security, this paper tries...

background: water is considered as the main source of life but water resources are limited and nonrenewable. different factors have caused groundwater to decrease. therefore, modeling and predicting groundwater level is of great importance. methods: monthly groundwater level data of about 20 years (october 1991 to february 2012) from the hamadan-bahar plain, west of iran were used based on peiz...

Based on wavelet packet decomposition and conditions of the support vector kernel function, a nonlinear wavelet basis is introduced to construct the kernel function of support vector machine (SVM). A tighten wavelet support vector machine (WSVM), which has strong generalization ability is also obtained. In this study, a novel damage classification method based on wavelet support vector machine ...

Groundwater level prediction in a water basin plays a significant role in the management of groundwater resources. Aground water level forecasting system is developed in this study using Support vector Machines (SVM). Further Quantum behaved Particle Swarm Optimization (QPSO) function is employed in this study to determine the SVM parameters. Later, the proposed SVM-QPSO model is used in determ...