Not an expert by any means, but the way I understand it is this (someone please correct me if I'm wrong):
In fuzzy logic, instead of saying something is either entirely true or entirely false, we say that it is entirely false, mostly false, equally true and false, mostly true, or entirely true. To do so, we represent these "degrees of truth" as numbers between $0$ and $1$. So, for example, if I were to say that my soup was cold with a degree of $0.7$, I'd be saying that it's fairly cold (certainly more cold than it is hot), but that it could have been colder. It's mostly cold.
Now, it is a beautiful day with a degree of $0.6$ (mostly beautiful, but we've seen better days), hot with a degree of $0.4$ (more cool than it is hot), and raining with a degree of $0.8$ (raining fairly hard, but we're not underwater yet). John will go to the park if it is beautiful, not hot, and not raining. Taking the complements of the negative conditions (hot, raining), we have the following degrees of truth: $0.6$, $0.6$, $0.2$.
So what is our degree of truth that John is going to the park? $0.2$ (John is going to the park, but probably not for very long). This is because the "not raining" condition is the condition that most limits John's trip to the park, as it is the least true. So the degree of truth that John is going to the park is $\min(0.6, 0.6, 0.2)$. Thinking about it more intuitively, if it were incredibly beautiful out and not at all hot, John would be no more eager to go to the park; it's still raining heavily, and that's really all that is necessary to deter John.