A Co-optimization PSO for Fuzzy Rule-Based Classifier Design Problem Based on Enlarged Hedge Algebras

Fuzzy Rule-Based Classifier (FRBC) design problem has been widely studied due to many practical applications. Hedge Algebras based Classifier Design Methods (HACDMs) are the outstanding and effective approaches because these approaches based on a mathematical formal formalism allowing the fuzzy sets based computational semantics generated from their inherent qualitative semantics of linguistic terms. HACDMs include two phase optimization process. The first phase is to optimize the semantic parameter values by applying an optimization algorithm. Then, in the second phase, the optimal fuzzy rule based system for FRBC is extracted based on the optimal semantic parameter values provided by the first phase. The performance of FRBC design methods depends on the quality of the applied optimization algorithms. This paper presents our proposed co-optimization Particle Swarm Optimization (PSO) algorithm for designing FRBC with trapezoidal fuzzy sets based computational semantics generated by Enlarged Hedge Algebras (EHAs). The results of experiments executed over 23 real world datasets have shown that Enlarged Hedge Algebras based classifier with our proposed co-optimization PSO algorithm outperforms the existing classifiers which are designed based on Enlarged Hedge Algebras methodology with two phase optimization process and the existing fuzzy set theory based classifiers

Tripod-supported offshore wind turbines: Modal and coupled analysis and a parametric study using X-SEA and FAST

This paper presents theoretical aspects and an extensive numerical study of the coupled analysis of tripod support structures for offshore wind turbines (OWTs) by using X-SEA and FAST v8 programs. In a number of site conditions such as extreme and longer period waves, fast installation, and lighter foundations, tripod structures are more advantageous than monopile and jacket structures. In the implemented dynamic coupled analysis, the sub-structural module in FAST was replaced by the X-SEA offshore substructure analysis component. The time-histories of the reaction forces and the turbine loads were then calculated. The results obtained from X-SEA and from FAST were in good agreement. The pile-soil-structure interaction (PSSI) was included for reliable evaluation of OWT structural systems. The superelement concept was introduced to reduce the computational time. Modal, coupled and uncoupled analyses of the NREL 5MW OWT-tripod support structure including PSSI were carried out and the discussions on the natural frequencies, mode shapes and resulted displacements are presented. Compared to the uncoupled models, the physical interaction between the tower and the support structure in the coupled models resulted in smaller responses. Compared to the fixed support structures, i.e., when PSSI is not included, the piled-support structure has lower natural frequencies and larger responses attributed to its actual flexibility. The models using pile superelements are computationally efficient and give results that are identical to the common finite element models

Adaptation options for agricultural cultivation systems in the South Central Coast under the context of climate change: Assessment Report.

This report highlights the results of consultation meetings and field visits organized by the Department of Crop Production and the CGIAR Research Program on Climate Change, Agriculture and Food Security in Southeast Asia in association with the three offices of the Department of Agriculture and Rural Development in the South Central Coast provinces of Binh Thuan, Ninh Thuan, and Khanh Hoa, in combination with consultation with the provinces in the conference: “Summing up crops production in the Winter-Spring season in 2018-2019, implementing the Summer-Autumn season, Main rice season in 2019 for the South Central Coast and the Central Highlands” held by the Ministry of Agriculture and Rural Development in Tam Ky City, Quang Nam Province on 12 April 2019. The meetings underlined the progress made by the provinces on climate change adaptation and mitigation, options for risk reductions in agricultural production, and conversion of crop structure as results of implementing the guidelines of the provinces and the Sector, especially, solutions for reservation and efficient and economic use of water under the context of climate change. This assessment report also reviews some issues related to the agricultural transformation of the region in adapting to risks caused by climate change. They are based on comparative advantages in terms of geographical location and market of key agricultural products. This report also points out shortcomings in using land and unreasonable points in managing and using important natural resources, especially water, and provides recommendations for the agricultural transformation and inter-regional connection with the Central Highlands and the Southeast. The team also introduces climate-related risks maps and adaptation plans (CS MAP) which is applied in the five provinces in the Mekong Delta Region, and hopes this solution’s expansion shall be supported by the Ministry of Agriculture and Rural Development and the provinces

A HEDGE ALGEBRAS BASED CLASSIFICATION REASONING METHOD WITH MULTI-GRANULARITY FUZZY PARTITIONING

During last years, lots of the fuzzy rule based classifier (FRBC) design methods have been proposed to improve the classification accuracy and the interpretability of the proposed classification models. Most of them are based on the fuzzy set theory approach in such a way that the fuzzy classification rules are generated from the grid partitions combined with the pre-designed fuzzy partitions using fuzzy sets. Some mechanisms are studied to automatically generate fuzzy partitions from data such as discretization, granular computing, etc. Even those, linguistic terms are intuitively assigned to fuzzy sets because there is no formalisms to link inherent semantics of linguistic terms to fuzzy sets. In view of that trend, genetic design methods of linguistic terms along with their (triangular and trapezoidal) fuzzy sets based semantics for FRBCs, using hedge algebras as the mathematical formalism, have been proposed. Those hedge algebras-based design methods utilize semantically quantifying mapping values of linguistic terms to generate their fuzzy sets based semantics so as to make use of fuzzy sets based-classification reasoning methods proposed in design methods based on fuzzy set theoretic approach for data classification. If there exists a classification reasoning method which bases merely on semantic parameters of hedge algebras, fuzzy sets-based semantics of the linguistic terms in fuzzy classification rule bases can be replaced by semantics - based hedge algebras. This paper presents a FRBC design method based on hedge algebras approach by introducing a hedge algebra- based classification reasoning method with multi-granularity fuzzy partitioning for data classification so that the semantic of linguistic terms in rule bases can be hedge algebras-based semantics. Experimental results over 17 real world datasets are compared to existing methods based on hedge algebras and the state-of-the-art fuzzy sets theoretic-based approaches, showing that the proposed FRBC in this paper is an effective classifier and produces good results

Structure and physico-chemical properties of silica gels doped with optically activated Er3+ ions by sol-gel process

This paper is devoted  to the study of the relationship between structure and optical properties of silica glasses doped with optically active Er3+ ions and reported the influence of the suitably selected heat treatment on the optical properties of silica glasses. The physico-chemical properties of Er3+doped silica are presented, which has been related with the effects of hydroxyl groups on the luminescence property  of Er3+ in the host matrix of silica

MEASURES TO IMPROVE THE LEARNING QUALITY OF BASKETBALL SUBJECT FOR NON-SPECIALIZED STUDENTS AT BAC NINH SPORTS UNIVERSITY OF VIETNAM UNDER THE CREDIT-BASED TRAINING SYSTEM

In using conventional scientific research methods in the field of physical training and sports, we selected and built the content of 04 measures to improve the quality of teaching Basketball subject for non-specialized students of Bac Ninh Sport University of Viet Nam under the credit-based training system, at the same time test the theory on the feasibility of measures by an expert method. The result showed that the selected and built measures were feasible and could be applied in practice to improve the quality of teaching Basketball subject for non-specialized students at Bac Ninh Sport University of Viet Nam under the credit-based training system.  Article visualizations

Assessment of seasonal winter temperature forecast errors in the regcm model over northern Vietnam

This study verified the seasonal six-month forecasts for winter temperatures for northern Vietnam in 1998–2018 using a regional climate model (RegCM4) with the boundary conditions of the climate forecast system Version 2 (CFSv2) from the National Centers for Environmental Prediction (NCEP). First, different physical schemes (land-surface process, cumulus, and radiation parameterizations) in RegCM4 were applied to generate 12 single forecasts. Second, the simple ensemble forecasts were generated through the combinations of those different physical formulations. Three subclimate regions (R1, R2, R3) of northern Vietnam were separately tested with surface observations and a reanalysis dataset (Japanese 55-year reanalysis (JRA55)). The highest sensitivity to the mean monthly temperature forecasts was shown by the land-surface parameterizations (the biosphere−atmosphere transfer scheme (BATS) and community land model version 4.5 (CLM)). The BATS forecast groups tended to provide forecasts with lower temperatures than the actual observations, while the CLM forecast groups tended to overestimate the temperatures. The forecast errors from single forecasts could be clearly reduced with ensemble mean forecasts, but ensemble spreads were less than those root-mean-square errors (RMSEs). This indicated that the ensemble forecast was underdispersed and that the direct forecast from RegCM4 needed more postprocessing