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82 results for “Learning Parameters”
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Research ArticleOpen accessIn the abstractParameter Optimization of Gradient Tree Boosting Using Dragonfly Algorithm in Crime Forecasting and AnalysisAlif Ridzuan Khairuddin, Nor Azizah Ali, Razana Alwee et al.Crime forecasting and analysis are very important in predicting future crime patterns and beneficial to the authorities in planning effective crime prevention measures. One of the challenges found in crime analysis is the crime data itself as its form, representation and distribution are varied and unpredictable. To handle such data, most researchers have been focusing on applying various Artificial Intelligence … …Journal of Computer Science, Vol. 15, Issue 8 · 7 Aug 2019 · 7,918 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Optimization of Physics Simulations Through Genetic AlgorithmsOksana Shadura, Federico Carminati, Anatoliy PetrenkoThe GeantV R&D approach is revisiting the standard particle transport simulation approach to be able to benefit from “Single Instruction, Multiple Data” (SIMD) computational architectures or extremely parallel systems like coprocessors and GPUs. The goal of this work is to develop a mechanism for optimizing the programs used for High-Energy Physics (HEP) particle transport simulations using a “black-box” optimization approach. … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 8,091 accessesView PDFCite
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Neuro-Fuzzy Inference System-Particle Swarm Optimization Based Stability Maintenance of Power System NetworksR. Latha, J. KanakarajDuring faulty condition voltage instability is one of the major crisis in power system networks. This study proposes a hybrid learning algorithm to improve the stability performance of a power system with Distributed Generations (DGs). Here the distribution system stability is maintained with reduced power loss using an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Particle Swarm Optimization (PSO) techniques. In … …American Journal of Applied Sciences, Vol. 10, Issue 8 · 24 Jul 2013 · 6,906 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision SupportS. Parkash Kumar, K. S. RamaswamiProblem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient … …Journal of Computer Science, Vol. 7, Issue 11 · 24 Aug 2011 · 6,671 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Analysis of Power Aware Congestion Control Multipath Multicast Protocol for Mobile Ad hoc NetworkDuraiswamy Karuppaswamy, Vijayaragavan ShanmugamProblem statement: In MANETs, wireless link transmission errors, mobility and congestion are major causes for packet loss. Mobility may cause packet loss in different ways. Whereas congestion in a network occurs, whenever the demands exceed the maximum capacity of a communication link especially when multiple hosts try to access a shared media simultaneously. Approach: In this study, we proposed a … …Journal of Computer Science, Vol. 6, Issue 12 · 2 Nov 2010 · 7,038 accessesView PDFCite
Research ArticleOpen accessIn the abstractNasal Administration of Quercetin Liposomes Modulate Cognitive Impairment and Inhibit Acetylcholinesterase Activity in HippocampusTerdthai Tong-Un, Supaporn Muchimapura, Wathita Phachonpai, Jintanaporn WattanathornProblem statement: Oxidative stress is a major factor implicated in the degeneration of cholinergic neurons in Alzheimer’s Disease (AD). Several reports have indicated that antioxidant intake is beneficial to delay or inhibit the progression of this disease. Presently, Acetylcholinesterase (AChE) inhibitors are the mainstay of therapy for AD. Quercetin, one of the flavonoids in fruits and vegetables, has a powerful … …Neuroscience International, Vol. 1, Issue 1 · 30 Jun 2010 · 7,170 accessesView PDFCite
Research ArticleOpen accessIn the abstractProsody Modification of Standard Arabic Speech Using Combining Synchronous Overlap and Add With Fixed-Synthesis Algorithm and Multi Level Discrete Wavelet TransformYkhlef Faycal, Bensebti Mesaoud, Bendaouia LotfiProblem statement: The objective of prosody modification is to change the amplitude, duration and pitch (F0) of speech segments without altering their spectral envelop. Applications are numerous, including, Text-To-Speech synthesis, transformation of voice characteristics and foreign language learning. Several approaches have been developed in the literature to achieve this goal. The main restrictions of these latter are in the modification … …Journal of Computer Science, Vol. 6, Issue 4 · 30 Apr 2010 · 6,836 accessesView PDFCite
Research ArticleOpen accessIn the abstractChange Detection Using Neural Network with Improvement Factor in Satellite ImagesM. A. Fkirin, S. M. Badwai, Sayed A. MohamedProblem statement: The aim of this study is to investigate the applicability of using the neural network techniques in change detection of remotely sensed data. Approach: In addition, the tuning parameters of the network, such as encoding the output classes, adding the momentum term and learning rate, are investigated in order to achieve best network performance. Results: Neural network-based change … …American Journal of Environmental Sciences, Vol. 5, Issue 6 · 31 Dec 2009 · 6,648 accessesView PDFCite