Precise customer requirements acquisition is the primary stage of product conceptual design, which plays a decisive role in product quality and innovation. However, existing customer requirements mining approaches pay attention to the offline or online customer comment feedback and there has been little quantitative analysis of customer requirements in the analogical reasoning environment. Latent and innovative customer requirements can be expressed by analogical inspiration distinctly. In response, this paper proposes a semantic analysis-driven customer requirements mining method for product conceptual design based on deep transfer learning and improved latent Dirichlet allocation (ILDA). Initially, an analogy-inspired verbal protocol analysis experiment is implemented to obtain detailed customer requirements descriptions of elevator. Then, full connection layers and a softmax layer are added to the output-end of Chinese bidirectional encoder representations from Transformers (BERT) pre-training language model. The above deep transfer model is utilized to realize the customer requirements classification among functional domain, behavioral domain and structural domain in the customer requirement descriptions of elevator by fine-tuning training. Moreover, the ILDA is adopted to mine the functional customer requirements that can represent customer intention maximally. Finally, an effective accuracy of customer requirements classification is acquired by using the BERT deep transfer model. Meanwhile, five kinds of customer requirements of elevator and corresponding keywords as well as their weight coefficients in the topic-word distribution are extracted. This work can provide a novel research perspective on customer requirements mining for product conceptual design through natural language processing.

As a natural and cultural heritage in the world,the slope of Longjing Road lies in the West Lake Scenic Area. However, this slope suffers from rain-wash, air-slake and later-on natural movements which cause collapse, thus the slope calls for engineering support. Yet the slopes we used to build are mainly aimed to construction engineering and highways particularly, that we must take their special locations into consideration. Their particularity demand that we should choose a certainly workable engineering support and design it in a way that delights people's eye at the meantime, therefore much more difficult work is to be done to meet it. Among those engineering support we know, retaining wall or anchor-type lattice beam is helpful in large-area virescence. Through rational design and beautification, it ensures the security and stability of the engineering support and meanwhile it helps with its pleasing outlook. By means of finite element strength reduction factor method, we analyze the stability of the slope on the Longjing Road with the finite element software and the effectiveness of retaining wall and anchor-type lattice beam. Also, through safety factors, displacement and destruction process, we compare the actual effectiveness of these two cases and work out some improvement measures. These results can serve as references in choosing engineering support schemes alike.Keywords-strength reduction of FEM; facter of security and stability; gravity retaining wall; anchor lattice beam;