![]() If you are expecting some kind of Wing Commander: Privateer-style story with plenty of structure, you won't find it here. You can follow the plot for a while, then go off and do something else, and then pick up the plotline later on, though this isn't as helpful as it seems. From there, you can try to follow the plot and see where it leads you, or you can just go off on your own and explore the many different sectors of the known universe, or both. You start alone in your little vessel and are given the hints of a plot involving a great and powerful ancient McGuffin that various factions are trying to control. Set in the distant future where humanity has colonized the stars and now rubs elbows with various alien species, X3 puts you in the role of Julian Brenner, the hero of X2. ![]() Welcome to deep space and the open-ended universe of X3: Reunion. X3 also features a single-player storyline to deliver some structure for those of us with shorter attention spans, though this doesn't pan out anywhere near as well. X3: Reunion, the latest game in the series, delivers some stunning visuals and more of that wide-open-ended gameplay, which is great if you're a fan of the genre. Rather than running through a series of scripted missions, you can explore the void, buy and sell goods for a profit, and battle the occasional bad guy. ![]() X has become the spiritual heir to Elite, the old-school, deeply open-ended space games that let you go off and do your own thing for hours at a time. ![]() In other words, they're beautiful to look at, but they also unfold at a snail's pace. Results of the present study provide decision supports for the emotional evaluation of the cockpit interior space.The X games (and we're referring not to the extreme-sports event, but to Egosoft's space exploration/trading/empire-building simulations) have always been a bit like the famous sci-fi movie 2001: A Space Odyssey. Obtained experimental results indicate that the GRNN not only has the highest classification accuracy but also has the highest stability in comparison to the other two neural networks, so that it is a more appropriate method for the emotional evaluation of the aircraft cockpit. Then, the three models are comprehensively compared through factors such as the model evaluation criteria, network structure, and network parameters. In this regard, the radical basis function neural network (RBFNN), Elman neural network (ENN), and the general regression neural network (GRNN) are applied to construct the sentimental prediction evaluation model. Moreover, several technologies and the Kansei engineering method are applied to acquire the cockpit interior emotional evaluation data for typical aircraft models. To this end, the neural network is applied to construct an emotional model to evaluate the emotional prediction of the interior design of the aircraft cockpit. In order to resolve this problem, a more efficient cockpit emotion evaluation system is established in the present study to simply and quickly obtain the cockpit emotion evaluation value. Studies show that there are shortcomings in applying conventional methods for the emotional evaluation of the aircraft cockpit.
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