Search results for: adaptive systems

Authors: Sven Rebhan, Nils Einecke, Julian Eggert

Abstract:

In this paper we propose a method for vision systems to consistently represent functional dependencies between different visual routines along with relational short- and long-term knowledge about the world. Here the visual routines are bound to visual properties of objects stored in the memory of the system. Furthermore, the functional dependencies between the visual routines are seen as a graph also belonging to the object-s structure. This graph is parsed in the course of acquiring a visual property of an object to automatically resolve the dependencies of the bound visual routines. Using this representation, the system is able to dynamically rearrange the processing order while keeping its functionality. Additionally, the system is able to estimate the overall computational costs of a certain action. We will also show that the system can efficiently use that structure to incorporate already acquired knowledge and thus reduce the computational demand.

Keywords: Adaptive systems, Knowledge representation, Machinevision, Systems engineering

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1651

Authors: Rungnapa Taithai, Anant Oonsivilai

Abstract:

This paper presents optimal based damping controllers of Unified Power Flow Controller (UPFC) for improving the damping power system oscillations. The design problem of UPFC damping controller and system configurations is formulated as an optimization with time domain-based objective function by means of Adaptive Tabu Search (ATS) technique. The UPFC is installed in Single Machine Infinite Bus (SMIB) for the performance analysis of the power system and simulated using MATLAB-s simulink. The simulation results of these studies showed that designed controller has an tremendous capability in damping power system oscillations.

Keywords: Adaptive Tabu Search (ATS), damping controller, Single Machine Infinite Bus (SMIB), Unified Power Flow Controller (UPFC).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2433

Authors: O. Hassanein, Sreenatha G. Anavatti, Tapabrata Ray

Abstract:

The dynamics of the Autonomous Underwater Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line adaptive fuzzy model and adaptive neural fuzzy network (ANFN) model techniques to overcome the uncertain external disturbance and the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according to the back propagation algorithm based upon the error between the identified model and the actual output of the plant. The proposed ANFN model adopts a functional link neural network (FLNN) as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN model is a nonlinear combination of input variables. Fuzzy control system is applied to guide and control the AUV using both adaptive models and mathematical model. Simulation results show the superiority of the proposed adaptive neural fuzzy network (ANFN) model in tracking of the behavior of the AUV accurately even in the presence of noise and disturbance.

Keywords: AUV, AUV dynamic model, fuzzy control, fuzzy modelling, adaptive fuzzy control, back propagation, system identification, neural fuzzy model, FLNN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2107

Authors: M. Polanský

Abstract:

This paper introduces a new method called ARPDC (Advanced Robust Parallel Distributed Compensation) for automatic control of nonlinear systems. This method improves a quality of robust control by interpolating of robust and optimal controller. The weight of each controller is determined by an original criteria function for model validity and disturbance appreciation. ARPDC method is based on nonlinear Takagi-Sugeno (T-S) fuzzy systems and Parallel Distributed Compensation (PDC) control scheme. The relaxed stability conditions of ARPDC control of nominal system have been derived. The advantages of presented method are demonstrated on the inverse pendulum benchmark problem. From comparison between three different controllers (robust, optimal and ARPDC) follows, that ARPDC control is almost optimal with the robustness close to the robust controller. The results indicate that ARPDC algorithm can be a good alternative not only for a robust control, but in some cases also to an adaptive control of nonlinear systems.

Keywords: Robust control, optimal control, Takagi–Sugeno (TS) fuzzy models, linear matrix inequality (LMI), observer, Advanced Robust Parallel Distributed Compensation (ARPDC).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1526

Authors: W. Chayinthu, K-N. Areerak, K-L. Areerak, A. Srikaew

Abstract:

This paper presents the optimal controller design of the generator control unit in the aircraft power system. The adaptive tabu search technique is applied to tune the controller parameters until the best terminal output voltage of generator is achieved. The output response from the system with the controllers designed by the proposed technique is compared with those from the conventional method. The transient simulations using the commercial software package show that the controllers designed from the adaptive tabu search algorithm can provide the better output performance compared with the result from the classical method. The proposed design technique is very flexible and useful for electrical aircraft engineers.

Keywords: Cascade PI controllers, DQ method, Adaptive tabusearch, Generator control unit, Aircraft power system, Modeling, Simulation, Artificial Intelligence.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2609

Authors: T Panigrahi, G Panda, Mulgrew

Abstract:

This paper introduces a new approach for the performance analysis of adaptive filter with error saturation nonlinearity in the presence of impulsive noise. The performance analysis of adaptive filters includes both transient analysis which shows that how fast a filter learns and the steady-state analysis gives how well a filter learns. The recursive expressions for mean-square deviation(MSD) and excess mean-square error(EMSE) are derived based on weighted energy conservation arguments which provide the transient behavior of the adaptive algorithm. The steady-state analysis for co-related input regressor data is analyzed, so this approach leads to a new performance results without restricting the input regression data to be white.

Keywords: Error saturation nonlinearity, transient analysis, impulsive noise.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1731

Authors: Carolina B. Baguio

Abstract:

One of the purposes of the robust method of estimation is to reduce the influence of outliers in the data, on the estimates. The outliers arise from gross errors or contamination from distributions with long tails. The trimmed mean is a robust estimate. This means that it is not sensitive to violation of distributional assumptions of the data. It is called an adaptive estimate when the trimming proportion is determined from the data rather than being fixed a “priori-. The main objective of this study is to find out the robustness properties of the adaptive trimmed means in terms of efficiency, high breakdown point and influence function. Specifically, it seeks to find out the magnitude of the trimming proportion of the adaptive trimmed mean which will yield efficient and robust estimates of the parameter for data which follow a modified Weibull distribution with parameter λ = 1/2 , where the trimming proportion is determined by a ratio of two trimmed means defined as the tail length. Secondly, the asymptotic properties of the tail length and the trimmed means are also investigated. Finally, a comparison is made on the efficiency of the adaptive trimmed means in terms of the standard deviation for the trimming proportions and when these were fixed a “priori". The asymptotic tail lengths defined as the ratio of two trimmed means and the asymptotic variances were computed by using the formulas derived. While the values of the standard deviations for the derived tail lengths for data of size 40 simulated from a Weibull distribution were computed for 100 iterations using a computer program written in Pascal language. The findings of the study revealed that the tail lengths of the Weibull distribution increase in magnitudes as the trimming proportions increase, the measure of the tail length and the adaptive trimmed mean are asymptotically independent as the number of observations n becomes very large or approaching infinity, the tail length is asymptotically distributed as the ratio of two independent normal random variables, and the asymptotic variances decrease as the trimming proportions increase. The simulation study revealed empirically that the standard error of the adaptive trimmed mean using the ratio of tail lengths is relatively smaller for different values of trimming proportions than its counterpart when the trimming proportions were fixed a 'priori'.

Keywords: Adaptive robust estimate, asymptotic efficiency, breakdown point, influence function, L-estimates, location parameter, tail length, Weibull distribution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2029

Authors: Xu Tao, Yilun Xu, Dingwei Xiang, Yaofei Sun

Abstract:

The practice of urban planning and construction based on the concept of the “low carbon eco-city” has been universally accepted by the academic community in response to urban issues such as population, resources, environment, and social development. Based on this, the current article first analyzes the concepts of low carbon eco-city, then builds a complex adaptive system (CAS) theory based on Chinese traditional philosophical thinking, and analyzes the adaptive relationship between material and non-material elements. A three-dimensional evaluation model of natural ecology, economic low carbon, and social harmony was constructed. Finally, the construction of a low carbon eco-city index system in Hexi Newtown of Nanjing was used as an example to verify the effectiveness of the research results; this paradigm provides a new way to achieve a low carbon eco-city system.

Keywords: Complex adaptive system, low carbon ecology, index system, model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 933

Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

Abstract:

This paper describes a new efficient blind source separation method; in this method we uses a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation (BSS), estimates, full-band, mixtures, Sub-band.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1729

Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

Abstract:

Mostly the systems are dealing with time varying signals. The Power efficiency can be achieved by adapting the system activity according to the input signal variations. In this context an adaptive rate filtering technique, based on the level crossing sampling is devised. It adapts the sampling frequency and the filter order by following the input signal local variations. Thus, it correlates the processing activity with the signal variations. Interpolation is required in the proposed technique. A drastic reduction in the interpolation error is achieved by employing the symmetry during the interpolation process. Processing error of the proposed technique is calculated. The computational complexity of the proposed filtering technique is deduced and compared to the classical one. Results promise a significant gain of the computational efficiency and hence of the power consumption.

Keywords: Level Crossing Sampling, Activity Selection, Rate Filtering, Computational Complexity, Interpolation Error.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1510

Authors: Priyanka Chaudhary, M. Rizwan

Abstract:

This paper presents a grid synchronization technique based on adaptive notch filter for SPV (Solar Photovoltaic) system along with MPPT (Maximum Power Point Tracking) techniques. An efficient grid synchronization technique offers proficient detection of various components of grid signal like phase and frequency. It also acts as a barrier for harmonics and other disturbances in grid signal. A reference phase signal synchronized with the grid voltage is provided by the grid synchronization technique to standardize the system with grid codes and power quality standards. Hence, grid synchronization unit plays important role for grid connected SPV systems. As the output of the PV array is fluctuating in nature with the meteorological parameters like irradiance, temperature, wind etc. In order to maintain a constant DC voltage at VSC (Voltage Source Converter) input, MPPT control is required to track the maximum power point from PV array. In this work, a variable step size P & O (Perturb and Observe) MPPT technique with DC/DC boost converter has been used at first stage of the system. This algorithm divides the dPpv/dVpv curve of PV panel into three separate zones i.e. zone 0, zone 1 and zone 2. A fine value of tracking step size is used in zone 0 while zone 1 and zone 2 requires a large value of step size in order to obtain a high tracking speed. Further, adaptive notch filter based control technique is proposed for VSC in PV generation system. Adaptive notch filter (ANF) approach is used to synchronize the interfaced PV system with grid to maintain the amplitude, phase and frequency parameters as well as power quality improvement. This technique offers the compensation of harmonics current and reactive power with both linear and nonlinear loads. To maintain constant DC link voltage a PI controller is also implemented and presented in this paper. The complete system has been designed, developed and simulated using SimPower System and Simulink toolbox of MATLAB. The performance analysis of three phase grid connected solar photovoltaic system has been carried out on the basis of various parameters like PV output power, PV voltage, PV current, DC link voltage, PCC (Point of Common Coupling) voltage, grid voltage, grid current, voltage source converter current, power supplied by the voltage source converter etc. The results obtained from the proposed system are found satisfactory.

Keywords: Solar photovoltaic systems, MPPT, voltage source converter, grid synchronization technique.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1915

Authors: P.Varzakas

Abstract:

In this paper, an accurate theoretical analysis for the achievable average channel capacity (in the Shannon sense) per user of a hybrid cellular direct-sequence/fast frequency hopping code-division multiple-access (DS/FFH-CDMA) system operating in a Rayleigh fading environment is presented. The analysis covers the downlink operation and leads to the derivation of an exact mathematical expression between the normalized average channel capacity available to each system-s user, under simultaneous optimal power and rate adaptation and the system-s parameters, as the number of hops per bit, the processing gain applied, the number of users per cell and the received signal-tonoise power ratio over the signal bandwidth. Finally, numerical results are presented to illustrate the proposed mathematical analysis.

Keywords: Shannon capacity, adaptive systems, code-division multiple access, fading channels.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1481

Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

Abstract:

This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of singleparameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: Hybrid fault diagnosis, Dynamic neural networks, Nonlinear systems.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2176

Authors: Awadhesh Kumar Singh

Abstract:

Checkpointing is one of the commonly used techniques to provide fault-tolerance in distributed systems so that the system can operate even if one or more components have failed. However, mobile computing systems are constrained by low bandwidth, mobility, lack of stable storage, frequent disconnections and limited battery life. Hence, checkpointing protocols having lesser number of synchronization messages and fewer checkpoints are preferred in mobile environment. There are two different approaches, although not orthogonal, to checkpoint mobile computing systems namely, time-based and index-based. Our protocol is a fusion of these two approaches, though not first of its kind. In the present exposition, an index-based checkpointing protocol has been developed, which uses time to indirectly coordinate the creation of consistent global checkpoints for mobile computing systems. The proposed algorithm is non-blocking, adaptive, and does not use any control message. Compared to other contemporary checkpointing algorithms, it is computationally more efficient because it takes lesser number of checkpoints and does not need to compute dependency relationships. A brief account of important and relevant works in both the fields, time-based and index-based, has also been included in the presentation.

Keywords: Checkpointing, forced checkpoint, mobile computing, recovery, time-coordinated.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1443

Authors: Behnam Mehrkian, Arash Bahar, Ali Chaibakhsh

Abstract:

Magneto-rheological (MR) fluid damper is a semiactive control device that has recently received more attention by the vibration control community. But inherent hysteretic and highly nonlinear dynamics of MR fluid damper is one of the challenging aspects to employ its unique characteristics. The combination of artificial neural network (ANN) and fuzzy logic system (FLS) have been used to imitate more precisely the behavior of this device. However, the derivative-based nature of adaptive networks causes some deficiencies. Therefore, in this paper, a novel approach that employ genetic algorithm, as a free-derivative algorithm, to enhance the capability of fuzzy systems, is proposed. The proposed method used to model MR damper. The results will be compared with adaptive neuro-fuzzy inference system (ANFIS) model, which is one of the well-known approaches in soft computing framework, and two best parametric models of MR damper. Data are generated based on benchmark program by applying a number of famous earthquake records.

Keywords: Benchmark program, earthquake record filtering, fuzzy logic, genetic algorithm, MR damper.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2059

Authors: Kyunghoon Kim, Sungjoon Shim, Jun Tae Kim, Jong Tae Kim

Abstract:

In a wireless communication system, a predistorter(PD) is often employed to alleviate nonlinear distortions due to operating a power amplifier near saturation, thereby improving the system performance and reducing the interference to adjacent channels. This paper presents a new adaptive polynomial digital predistorter(DPD). The proposed DPD uses Coordinate Rotation Digital Computing(CORDIC) processors and PD process by pipelined architecture. It is simpler and faster than conventional adaptive polynomial DPD. The performance of the proposed DPD is proved by MATLAB simulation.

Keywords: DPD, CORDIC.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1739

Authors: Mohammad Ali Tabarzad, Caro Lucas, Ali Hamzeh

Abstract:

Adaptive Genetic Algorithms extend the Standard Gas to use dynamic procedures to apply evolutionary operators such as crossover, mutation and selection. In this paper, we try to propose a new adaptive genetic algorithm, which is based on the statistical information of the population as a guideline to tune its crossover, selection and mutation operators. This algorithms is called Statistical Genetic Algorithm and is compared with traditional GA in some benchmark problems.

Keywords: Genetic Algorithms, Statistical Information ofthe Population, PAUX, SSO.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1692

Authors: Franco Frattolillo

Abstract:

The advances in multimedia and networking technologies have created opportunities for Internet pirates, who can easily copy multimedia contents and illegally distribute them on the Internet, thus violating the legal rights of content owners. This paper describes how a simple and well-known watermarking procedure based on a spread spectrum method and a watermark recovery by correlation can be improved to effectively and adaptively protect MPEG-2 videos distributed on the Internet. In fact, the procedure, in its simplest form, is vulnerable to a variety of attacks. However, its security and robustness have been increased, and its behavior has been made adaptive with respect to the video terminals used to open the videos and the network transactions carried out to deliver them to buyers. In fact, such an adaptive behavior enables the proposed procedure to efficiently embed watermarks, and this characteristic makes the procedure well suited to be exploited in web contexts, where watermarks usually generated from fingerprinting codes have to be inserted into the distributed videos “on the fly", i.e. during the purchase web transactions.

Keywords: Copyright protection, digital watermarking, intellectualproperty protection.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1335

Authors: S. A. Gawish, F. A. Khalifa, R. M. Mostafa

Abstract:

This paper presents Simulation and experimental study aimed at investigating the effectiveness of an adaptive artificial neural network stabilizer on enhancing the damping torque of a synchronous generator. For this purpose, a power system comprising a synchronous generator feeding a large power system through a short tie line is considered. The proposed adaptive neuro-control system consists of two multi-layered feed forward neural networks, which work as a plant model identifier and a controller. It generates supplementary control signals to be utilized by conventional controllers. The details of the interfacing circuits, sensors and transducers, which have been designed and built for use in tests, are presented. The synchronous generator is tested to investigate the effect of tuning a Power System Stabilizer (PSS) on its dynamic stability. The obtained simulation and experimental results verify the basic theoretical concepts.

Keywords: Adaptive artificial neural network, power system stabilizer, synchronous generator.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1415

Authors: Joseph C. Chen, Venkata Mohan Kudapa

Abstract:

Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: Surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 417

Authors: K. Parandhama Gowd

Abstract:

Space technologies have changed the way we live in the present day society and manage many aspects of our daily affairs through Remote sensing, Navigation & Communications. Further, defense and military usage of spacecraft has increased tremendously along with civilian purposes. The number of satellites deployed in space in Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and the Geostationary Orbit (GEO) has gone up. The dependency on remote sensing and operational capabilities are most invariably to be exploited more and more in future. Every country is acquiring spacecraft in one way or other for their daily needs, and spacecraft numbers are likely to increase significantly and create spacecraft traffic problems. The aim of this research paper is to propose innovative design concepts for adaptive spacecraft. The main idea here is to improve existing design methods of spacecraft design and development to further improve upon design considerations for futuristic adaptive spacecraft with inbuilt features for automatic adaptability and self-protection. In other words, the innovative design considerations proposed here are to have future spacecraft with self-organizing capabilities for orbital control and protection from anti-satellite weapons (ASAT). Here, an attempt is made to propose design and develop futuristic spacecraft for 2030 and beyond due to tremendous advancements in VVLSI, miniaturization, and nano antenna array technologies, including nano technologies are expected.

Keywords: Satellites, low earth orbit, medium earth orbit, geostationary earth orbit, self-organizing control system, anti-satellite weapons, orbital control, radar warning receiver, missile warning receiver, laser warning receiver, attitude and orbit control systems, command and data handling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 958

Authors: Xinyue Zhao, Yutaka Satoh, Hidenori Takauji, Shun'ichi Kaneko

Abstract:

A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera. The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental results show the good performance of the proposed method.

Keywords: Hybrid feature, adaptive Particle Filter, robust Object Tracking, Grayscale Arranging Pairs (GAP) feature.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1479

Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

Abstract:

Efficient matrix-vector multiplication with diagonal sparse matrices is pivotal in a multitude of computational domains, ranging from scientific simulations to machine learning workloads. When encoded in the conventional Diagonal (DIA) format, these matrices often induce computational overheads due to extensive zero-padding and non-linear memory accesses, which can hamper the computational throughput, and elevate the usage of precious compute and memory resources beyond necessity. The ’DIA-Adaptive’ approach, a methodological enhancement introduced in this paper, confronts these challenges head-on by leveraging the advanced parallel instruction sets embedded within Machine Learning Units (MLUs). This research presents a thorough analysis of the DIA-Adaptive scheme’s efficacy in optimizing Sparse Matrix-Vector Multiplication (SpMV) operations. The scope of the evaluation extends to a variety of hardware architectures, examining the repercussions of distinct thread allocation strategies and cluster configurations across multiple storage formats. A dedicated computational kernel, intrinsic to the DIA-Adaptive approach, has been meticulously developed to synchronize with the nuanced performance characteristics of MLUs. Empirical results, derived from rigorous experimentation, reveal that the DIA-Adaptive methodology not only diminishes the performance bottlenecks associated with the DIA format but also exhibits pronounced enhancements in execution speed and resource utilization. The analysis delineates a marked improvement in parallelism, showcasing the DIA-Adaptive scheme’s ability to adeptly manage the interplay between storage formats, hardware capabilities, and algorithmic design. The findings suggest that this approach could set a precedent for accelerating SpMV tasks, thereby contributing significantly to the broader domain of high-performance computing and data-intensive applications.

Keywords: Adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 118

Authors: Oğuzhan Hasançebi, Saeid Kazemzadeh Azad

Abstract:

Keywords: Structural design optimization, optimal sizing, metaheuristics, self-adaptive step-size search, steel trusses, steel frames.}

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1373

Authors: Abiodun M. Aibinu, Momoh J. E. Salami, Amir A. Shafie, Athaur Rahman Najeeb

Abstract:

In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. These technique was subsequently used to determine the coefficients of Autoregressive Moving Average (ARMA) and Autoregressive (AR) system. The results obtained by introducing sequential and batch method of weight initialization, batch method of weight and coefficient update, adaptive momentum and learning rate technique gives more accurate result and significant reduction in convergence time when compared t the traditional method of back propagation algorithm, thereby making FFBPNN an appropriate technique for online ARMA coefficient determination.

Keywords: Adaptive Learning rate, Adaptive momentum, Autoregressive, Modeling, Neural Network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1448

Authors: Mohammad Shams Esfand Abadi, Nader Hadizadeh Kashani, Vahid Mehrdad

Abstract:

In this paper we present a general formalism for the establishment of the family of selective regressor affine projection algorithms (SR-APA). The SR-APA, the SR regularized APA (SR-RAPA), the SR partial rank algorithm (SR-PRA), the SR binormalized data reusing least mean squares (SR-BNDR-LMS), and the SR normalized LMS with orthogonal correction factors (SR-NLMS-OCF) algorithms are established by this general formalism. We demonstrate the performance of the presented algorithms through simulations in acoustic echo cancellation scenario.

Keywords: Adaptive filter, affine projection, selective regressor.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1525

Authors: Rajesh S.Prasad, U. V. Kulkarni, Jayashree.R.Prasad

Abstract:

As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance.

Keywords: Artificial Neural Networks (ANN); Computational Intelligence (CI); Connectionist Text Summarizer ECTS (ECTS); Evolving Connectionist systems; Evolving systems; Fuzzy systems (FS); Part of Speech (POS) disambiguation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1541

Authors: Mesfer Al Duhayyim, Paul Newbury

Abstract:

This paper proposes an effective adaptive e-learning system that uses a coloured concept map to show the learner's knowledge level for each concept in the chosen subject area. A Fuzzy logic system is used to evaluate the learner's knowledge level for each concept in the domain, and produce a ranked concept list of learning materials to address weaknesses in the learner’s understanding. This system obtains information on the learner's understanding of concepts by an initial pre-test before the system is used for learning and a post-test after using the learning system. A Fuzzy logic system is used to produce a weighted concept map during the learning process. The aim of this research is to prove that such a proposed novel adapted e-learning system will enhance learner's performance and understanding. In addition, this research aims to increase participants' overall understanding of their learning level by providing a coloured concept map of understanding followed by a ranked concepts list of learning materials.

Keywords: Adaptive e-learning system, coloured concept map, fuzzy logic, ranked concept list.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1034

Authors: Kang-Le Guan, Seung-Jae Lee, Myeon-Song Choi

Abstract:

The protection issues in distribution systems with open and closed-loop are studied, and a generalized protection setting scheme based on the traditional over current protection theories is proposed to meet the new requirements. The setting method is expected to be easier realized using computer program, so that the on-line adaptive setting for coordination in distribution system can be implemented. An automatic setting program is created and several cases are taken into practice. The setting results are verified by the coordination curves of the protective devices which are plotted using MATLAB.

Keywords: protection setting, on-line system analysis, over current protection, closed-loop distribution system

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2120

Authors: Hafizullah A. Hashim, Aniza. A

Abstract:

The Spiral development model has been used successfully in many commercial systems and in a good number of defense systems. This is due to the fact that cost-effective incremental commitment of funds, via an analogy of the spiral model to stud poker and also can be used to develop hardware or integrate software, hardware, and systems. To support adaptive, semantic collaboration between domain experts and knowledge engineers, a new knowledge engineering process, called Spiral_OWL is proposed. This model is based on the idea of iterative refinement, annotation and structuring of knowledge base. The Spiral_OWL model is generated base on spiral model and knowledge engineering methodology. A central paradigm for Spiral_OWL model is the concentration on risk-driven determination of knowledge engineering process. The collaboration aspect comes into play during knowledge acquisition and knowledge validation phase. Design rationales for the Spiral_OWL model are to be easy-to-implement, well-organized, and iterative development cycle as an expanding spiral.

Keywords: Domain Expert, Knowledge Base, Ontology, Software Process.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1719