Showing papers in "Engineering Applications of Artificial Intelligence in 2012"

TL;DR: A bibliographical review over the last decade is presented on the application of Bayesian networks to dependability, risk analysis and maintenance and an increasing trend of the literature related to these domains is shown.

TL;DR: The study suggests that feed forward neural networks can be used as a viable alternative to physical-based models to simulate the responses of the aquifer under plausible future scenarios or to reconstruct long periods of missing observations provided past data for the influencing variables is available.

TL;DR: The survey found out that some well-known smart home applications like video based security applications has seen the maturity in terms of new research directions while some topics like smart homes for energy efficiency and video summarization are gaining momentum.

TL;DR: A novel fractional order fuzzy Proportional-Integral-Derivative (PID) controller is proposed in this paper which works on the closed loop error and its fractional derivative as the input and has a fractional integrator in its output.

TL;DR: A new decision making approach for group multi-criteria supplier selection problem, which clubs supplier selection process with order allocation for dynamic supply chains to cope market variations is presented.

TL;DR: A hybrid two stage one-against-all Support Vector Machine (SVM) approach is proposed for the automated diagnosis of defective rolling element bearings, which can be performed using simulation data, describing the dynamic response of defectiverolling element bearings.

TL;DR: The investigation results demonstrate that the proposed fusion prognostic framework is an effective forecasting tool that can integrate the strengths of both the data-driven method and the model-based particle filtering approach to achieve more accurate state forecasting.

TL;DR: The paper provides an overview of some of the principles found in nature and biology and analyses the effectiveness of bio-inspired methods, which are used to enhance multi-agent systems to solve complex engineering problems, especially in the manufacturing field.

TL;DR: On two sets with 24 and 30 LRP-2E instances, MS-ILS outperforms on average two GRASP algorithms and adding PR brings a further improvement, and the metaheuristic surpasses a tabu search on 30 instances for a more general problem with several main depots.

TL;DR: This work proposes a Swarm Intelligence approach to find successful cycle programs of traffic lights and obtains significant profits in terms of two main indicators: the number of vehicles that reach their destinations on time and the global trip time.

TL;DR: The comparison results indicate that the conjunction method could increase the forecast accuracy and perform better than the single support vector machine for one-day-ahead precipitation forecasting.

TL;DR: A new multi-objective optimization algorithm based on modified teaching-learning-based optimization (MTLBO) algorithm in order to solve the optimal location of automatic voltage regulators in distribution systems at presence of distributed generators (DGs).

TL;DR: A novel distributed multi-agent system using auctions based negotiation (DMAS/ABN) approach for resolving the resource conflicts and allocating multiple different types of shared resources amongst multiple competing projects and winner determination problem is solved by efficient new heuristic.

TL;DR: Simulation and experimental results show the advantages of the designed PSO-tuned PID-type FLC structures in terms of efficiency and robustness.

TL;DR: This paper proposes an effective scheduling method based on Best-so-far Artificial Bee Colony (Best- so-far ABC) for solving the JSSP and demonstrates that the proposed method is able to produce higher quality solutions than the current state-of theart heuristic-based algorithms.

TL;DR: The modified gravitational search algorithm (MGSA) is proposed, which aims to control the global exploration ability of the original algorithm, increase its convergence rate and thereby to obtain an acceptable solution with a lower number of iterations.

TL;DR: Fuzzy Lyapunov Synthesis is extended to the design of Type-1 and Type-2 Fuzzy Logic Controllers for nonsmooth mechanical systems and the output regulation problem for a servomechanism with nonlinear backlash is proposed as a case of study.

TL;DR: Five different variants of harmony search algorithm are studied by giving special attention to Self-adaptive Global Best Harmony Search (SGHS) algorithm, which lends itself very well to the training of NNs and also highly competitive with the compared methods in terms of classification accuracy.

TL;DR: A model for the joint design of ecodriving and timetable under uncertainty for high speed lines is proposed where the railway operator and administrator requirements are incorporated and it is compared to the current commercial service in order to evaluate the potential energy savings.

TL;DR: Results show that ACO optimization algorithm can automatically obtain the optimal parameters, C and @c, of the SVR model with very high predictive accuracy, and are suitable for on-line and real-time modeling NO"x emissions from coal-fired utility boilers.

TL;DR: In this paper, agent-oriented software development (AOSD) and MDE paradigms are fully integrated for the development of MAS and meta-modeling techniques are explicitly used to speed up several phases of the process.

TL;DR: Experimental results indicate that the proposed method outperforms other fire detection algorithms, providing high reliability and a low false alarm rate.

TL;DR: The paper has proposed solution applying the additional neural network responsible for the final forecast (integration of all particular prediction results), and the numerical experiments for prediction of the daily concentration of the PM"1"0 pollution in Warsaw are presented.

TL;DR: A new method for Emotion Recognition from Facial Expression using Fuzzy Inference System (FIS) is proposed, which is even able to recognize emotions from Partially Occluded Facial Images.

TL;DR: Experimental classification results show that the dimension reduction process performed by PCA has improved the classification of heart sound signals.

TL;DR: The research discussed the strong points of new method based on neurofuzzy and limbic system structure against classical and other intelligent methods and confirmed the significance of structural brain modeling beyond the classical artificial neural networks.

TL;DR: A new scheme for clustering gene expression datasets based on a modified version of Quantum-behaved Particle Swarm Optimization (QPSO) algorithm, known as the Multi-Elitist QPSO (MEQPSo) model, which employs a one-step K-means operator to effectively accelerate the convergence speed of the algorithm.

TL;DR: A hybrid Adaptive Neural Network-Particle Swarm Optimization (ANN-PSO) algorithm is being proposed for harmonic isolation that provides uniform convergence with the convergence rate comparable that of Adaline algorithm.

TL;DR: The results have demonstrated that the GEP model performs well with coefficient of correlation, mean and probability density at 50% equivalent to 0.94, 0.96 and 1.01, indicating that the proposed model predicts pile capacity accurately.

TL;DR: The proposed on-line learning algorithm updates the weights and biases of the neural network using the error between the set-point and the real output to show a satisfactory tracking performance in the presence of inversion errors caused by model uncertainty.