![]() The method has demonstrated its practicability and scientific feasibility, it also shows the potential to be adopted and extended for other domains when dealing with multi-objective holistic design making. A case study was performed to illustrate the details on how to apply knowledge query to provide a series of design alternatives autonomously by taking different design parameters into account. A prototypical ontology-based decision tool has been developed, aiming at the holistic optimization for energy pile system by combining ontology and Semantic Web Rule Language rules. This paper presents a novel multi-objective holistic approach for energy pile system design using ontology based multi-domain knowledge orchestration, which can holistically provide the designers with across domain factors regarding financial, safety, and environmental impact, for smart and holistic consideration during the early design stage. The cost for life cycle design, construction and maintenance, return of investment, CO2 emission related sustainable requirements, and so on also need to be considered, in a systematic manner, along with the main functional design objective for loading capacity and robustness. The traditional way of designing energy pile system is mostly single domain/objective oriented, which lacks of means to coherently consider different while relevant factors across domains. The ViLO ontology is supposed to be a basis for further constructions of domain ontologies and arti¯cial intelligence applications in Vietnamese law. The resulting ontology was demonstrated to be reliable and enriched. Through FOCA-based validation results, the proposed method was shown to be e®ective and e±cient. The method of the NeOn-based collaborations among domain experts and ontology engineers was conducted to build up the ViLO ontology. ![]() The ViLO ontology mainly consists of related institutions of Vietnamese political system, types and structures of legal documents. This study proposes a core ontology for Vietnamese legal documents which covers general legal domain called as ViLO. With the needs for legal information management in smart applications, especially for Vietnamese law, it is vitally important to construct core legal ontologies for knowledge representation. Innovative systems and ontologies in the law hold potential to conduct legal research. Legal ontologies play a key role in various legal applications and have been broadly used by many stakeholders. ![]() The benefit of the proposed method includes a short translation time and fewer mistranslations. The findings of the experiment show the effectiveness of the proposed method in achieving the design expectation. The objective of feature transfer learning is to reuse the past knowledge obtained in the form of dataset to be utilized for another target data. On the basis of preprocessing English-Chinese translation text data, features of English-Chinese translation text are extracted, features of English-Chinese translation text are rapidly classified by feature transfer learning, and machine models of English-Chinese translation are constructed based on the classification results. On the basis of analyzing the basic principles and specific strategies of English-Chinese machine translation, the traditional neural machine translation methods are analyzed, and then the translation process is optimized by transfer learning. In order to solve the problems of time-consuming and frequent mistranslations in traditional translation methods, this study designed an English-Chinese machine translation method based on transfer learning.
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