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Virtual Analyzers for MI and Density Based on Neural Networks Improved through an Integrated Strategy Involving a constructive algorithm and Definition of Initial Weights

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MACROMOLECULAR REACTION ENGINEERING 2023年第4期17卷 2200066-2200066页

作者： da Silva, Adilton Lopes Fontes, Cristiano Hora Embirucu, Marcelo Linear Polyethylene Unit Braskem Co BR-42816200 Camacari BA Brazil Univ Fed Bahia Polytech Inst Ind Engn Program BR-40210630 Salvador BA Brazil

This work presents the development and validation of two virtual analyzers (density and Melt Index (MI)) for quality monitoring and control of the final product in an industrial unit of Linear Polyethylene (LPE). Both models are based on Feedforward Neural Networks which are improved through a strategy involving the initial estimation of weights and a constructive algorithm to define the number of hidden units. The initialization strategy is based on linearization of the neural model with only one hidden unit (nonlinear model) and subsequent optimization of this model by maximizing its similarity to the standard linear regression model whose solution is obtained analytically. The Initial Neural Model (INM) is then used as a starting point for a gradual increase in the number of hidden units. In a validation test involving MI and density values collected over 2 years of operation, the neural model is able to predict these properties with mean percentage errors equal to 0.81% (MI) and 0.04% (density) and determination coefficients equal to 0.970 (MI) and 0.983 (density). The population coefficient estimated in all tests involving grade transitions (0.96) shows a strong linear correlation between the proposed model and laboratory measurements.

关键词： constructive algorithm feedforward neural network linear polyethylene quality parameters virtual analyser

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A constructive algorithm for Neural Networks Inspired on Decision Trees and Evolutionary algorithms

A Constructive Algorithm for Neural Networks Inspired on Dec...

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International Joint Conference on Neural Networks

作者： Marcus Vinicius Mazega Figueredo Emerson Cabrera Paraiso Julio Cesar Nievola PPGIA - PUCPR PPGIA-PUCPR

ISBN: (纸本)9781509006212

Inspired on decision trees and evolutionary algorithms, this paper proposes a learning algorithm of constructive neural networks that relies on three principles: to layout the neurons in a tree-like structure;to train each neuron individually;and, to optimize all the weights using an evolutionary approach. This way, it is expected to advance in two main questions concerning multilayer perceptrons (MLPs): how to determine the network architecture and how to build models that are more comprehensible. Based on the normalized information gain of each attribute, the algorithm builds the network architecture. In the process, it automatically creates a set of training examples for each individual neuron and executes single-cell learning. Once the network is created and trained, particle swarm optimization is utilized to evolve the connections of the network. Five metrics were utilized to validate the method when compared to decision trees and MLPs: accuracy, sensitivity, specificity, precision and comprehensibility. The experiments were executed in thirteen different databases and the results suggest that the proposed algorithm can generate neural networks with good classification performance and more comprehensible.

关键词： Knowledge extraction from neural networks Decision trees Evolutionary algorithms Decision Trees evolutionary algorithm NETWORK STRUCTURE Neural network constructive algorithm information gain Neurons Respiratory Inspiration learning algorithms

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A constructive algorithm for the Lovasz Local Lemma on permutations 14

A constructive algorithm for the Lovasz Local Lemma on permu...

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Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete algorithms

作者： David G. Harri Aravind Srinivasan Department of Applied Mathematics University of Maryland Department of Computer Science and Institute for Advanced Computer Studies University of Maryland

ISBN: (纸本)9781611973389

While there has been significant progress on algorithmic aspects of the Lovasz Local Lemma (LLL) in recent years, a noteworthy exception is when the LLL is used in the context of random permutations: the "lopsided" version of the LLL is usually at play here, and we do not yet have sub-exponential-time algorithms. We resolve this by developing a randomized polynomial-time algorithm for such applications. A noteworthy application is for Latin Transversals: the best-known general result here (Bissacot et al., improving on Erdos and Spencer), states that any n × n matrix in which each entry appears at most (27=256)n times, has a Latin transversal. We present the first polynomial-time algorithm to construct such a transversal. Our approach also yields RNC algorithms: for Latin transversals, as well as the first efficient ones for the strong chromatic number and (special cases of) acyclic edge-coloring.

关键词： low light constructive algorithm Permutation Transverse Lemma Latin algorithms

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A Novel constructive algorithm for CANet

A Novel Constructive Algorithm for CANet

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International Joint Conference on Neural Networks

作者： Danilo C. Pereira Bruno J. T. Fernandes Polytechnic School of Pernambuco University of Pernambuco

ISBN: (纸本)9781509061839

Theories inspired by the working and the structure of the human brain have been applied in various problems in computer vision, such as Artificial Neural Networks (ANNs). The concept of receptive and inhibitory fields have been adopted with success to improve the capability of the ANNs and are present in the deep learning models, such as ConvNet and LIPNet, that have been successfully used in many computer vision tasks. However, both shallow and deep ANN models need some expertise to define their architecture, as well as the definition of some of their parameters. A recently introduced ANN, called CANet, embeds the concepts of receptive fields, lateral inhibition, and autoassociative memory using a constructive algorithm that requires few parameters to perform its learning process. This paper presents a new constructive-pruning algorithm for CANet that contains even fewer parameters and can self-choose the quantity of neurons in the constructive layer of the model, called CANet-2. Also, we analyze the behavior of the model with the use of activation functions from the ReLU family in its constructive layer. Experiments in facial expression recognition showed that the proposed constructive algorithm along with the SoftPlus activation function improved CANet-2 in relation to the original version.

关键词： constructive algorithm images computer vision Artificial neural networks wetware role model Model structures constructivity

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constructive algorithms for structure learning in feedforward neural networks for regression problems

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IEEE TRANSACTIONS ON NEURAL NETWORKS 1997年第3期8卷 630-645页

作者： Kwok, TY Yeung, DY Department of Computer Science Hong Kong University of Science and Technology Kowloon Hong Kong China

In this survey paper, we review the constructive algorithms for structure learning in feedforward neural networks for regression problems, The basic idea is to start with a small network, then add hidden units and weights incrementally until a satisfactory solution is found, By formulating the whole problem as a state-space search, we first describe the general issues in constructive algorithms, with special emphasis on the search strategy, A taxonomy, based on the differences in the state transition mapping, the training algorithm, and the network architecture, is then presented.

关键词： cascade-correlation constructive algorithm dynamic node creation group method of data handling projection pursuit regression resource-allocating network state-space search structure learning

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Priority-based constructive algorithms for scheduling agile earth observation satellites with total priority maximization

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EXPERT SYSTEMS WITH APPLICATIONS 2016年 51卷 195-206页

作者： Xu, Rui Chen, Huaping Liang, Xinle Wang, Huimin Hohai Univ Sch Business Nanjing 211100 Jiangsu Peoples R China Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026 Peoples R China

This paper investigated an Earth observation scheduling problem for agile satellites under a time window constraint and resource constraints of limited on-board memory capacity and consecutive working time. We assumed that different observation tasks may have priority levels, and the objective is to maximize the total priority of selected tasks. To address the problem, we first presented a detailed problem description and developed a mathematical programming model. Considering the over-constrained feature of the problem, we developed constructive algorithms to solve the problem, which adopt a priority-based sequential construction procedure to avoid conflicts and generate feasible solutions. The proposed sequential construction procedure contributes to eliminating the need for extra constraint handling techniques, and helps to reduce the complexity of feasibility checking. By analyzing the competitive relationship of various resources, we proved the condition of mutual exclusion of time windows and then developed new priority-based indicators to evaluate the benefits and opportunity costs of different positioning decisions, which is a key component to be used in the proposed constructive algorithms. Through extensive computational experiments on various scenarios including real-world data from China's satellite platform, the effectiveness of the developed constructive algorithms was verified. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Agile earth observation satellite Scheduling constructive algorithm Ant colony optimization Heuristic

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Two constructive algorithms to Address a Multi-Depot Home Healthcare Routing Problem

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IETE JOURNAL OF RESEARCH 2022年第2期68卷 1108-1114页

作者： Bahadori-Chinibelagh, Soraya Fathollahi-Fard, Amir Mohammad Hajiaghaei-Keshteli, Mostafa Shomal Univ Dept Ind Engn Amol Iran Amirkabir Univ Technol Dept Ind Engn & Management Syst Tehran Iran Univ Sci & Technol Mazandaran Dept Ind Engn Behshahr Iran

Nowadays, there is a great deal of attention about the care of aging population. This motivates the home healthcare services to provide nursing and general hygiene cares at patient home for elderly persons in a situation of dependency. The routing decisions of caregivers to specify the assignment of patients and their sequence for visits are very important for related companies to reduce the transportation costs. Hence, this study proposes a novel multi-depot home healthcare routing model with the supposition of controlling the overall distance. Another contribution of this research is to propose two simple constructive algorithms to solve the developed problem. Finally, results confirm the efficiency of the second developed algorithm as well as the performance of the proposed model during different problem complexities.

关键词： Caregivers constructive algorithm Home healthcare Multi-depot routing problem Transportation cost

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A New Data Mining Scheme Using Artificial Neural Networks

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SENSORS 2011年第5期11卷 4622-4647页

作者： Kamruzzaman, S. M. Sarkar, A. M. Jehad Hankuk Univ Foreign Studies Dept Elect Engn Yongin 449791 Kyonggi Do South Korea Hankuk Univ Foreign Studies Dept Digital Informat Engn Yongin 449791 Kyonggi Do South Korea

Classification is one of the data mining problems receiving enormous attention in the database community. Although artificial neural networks (ANNs) have been successfully applied in a wide range of machine learning applications, they are however often regarded as black boxes, i.e., their predictions cannot be explained. To enhance the explanation of ANNs, a novel algorithm to extract symbolic rules from ANNs has been proposed in this paper. ANN methods have not been effectively utilized for data mining tasks because how the classifications were made is not explicitly stated as symbolic rules that are suitable for verification or interpretation by human experts. With the proposed approach, concise symbolic rules with high accuracy, that are easily explainable, can be extracted from the trained ANNs. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and the accuracy. The effectiveness of the proposed approach is clearly demonstrated by the experimental results on a set of benchmark data mining classification problems.

关键词： data mining neural networks symbolic rules weight freezing constructive algorithm pruning clustering rule extraction symbolic rules

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Training MLPs layer by layer using an objective function for internal representations

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NEURAL NETWORKS 1996年第1期9卷 83-97页

作者： Lengelle, R Denoeux, T UNIV TECHNOL COMPIEGNE CNRS URA 817 HEUDIASYE F-60206 COMPIEGNE FRANCE LYONNAISE EAUX LAB INFORMAT AVANCEE COMPIEGNE FRANCE

A new constructive algorithm for designing and training multilayer perceptrons is proposed. This algorithm involves the optimization of an objective function for internal representations, which does not require any computation of the network's outputs. Coupled with a strategy for recruiting units during the learning process, this concept provides a scheme for training a multilayer network layer by layer, until self-encoding of the pattern categories is achieved in the final, highest-level representations. Two objective functions are proposed For discrimination problems, recent experimental and theoretical results concerning back-propagation training of networks with one hidden layer and linear outputs suggest the introduction of a particular measure of class separability. For problems involving the approximation of a continuous function, we show that the minimization of the mean squared output error can be achieved by maximizing a statistical measure (the sample coefficient of multiple determination) in the last hidden layer. Simulations are used to illustrate the process of network construction, and to demonstrate the improvements brought by this approach over back-propagation in terms of performance and robustness.

关键词： multilayer perceptrons learning algorithm internal representation architecture constructive algorithm classification approximation discriminant analysis

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Influence of dissipations on parametric oscillations

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DOKLADY PHYSICS 2010年第11期55卷 564-567页

作者： Akulenko, L. D. Nesterov, S. V. Russian Acad Sci Ishlinskii Inst Problems Mech Moscow 119526 Russia

Complete investigation into the problem of parametric oscillations of a system in the presence of dissipation is carried out. Based on the numerical-analytical method, the boundaries of stability regions are constructed in a wide range of varying modulation coefficients and linear friction. It was implicitly assumed that the instability regions are maximal, while the actual presence of small dissipation leads to their narrowing. Modern software allows one to effectively construct the desired solutions of different classes of complex multi-parametric problems. This is achieved using the constructive algorithms based on the accelerated convergence method and continuation procedures by known parameters of the system in admissible regions of their variation.

关键词： step-by-step approach accelerating convergence Maximal wide-range narrowing system parameter optical coherence tomography angiography device constructivity constructive algorithm Parametric oscillation Depletion

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