Codes of emergent treatment in vaccine inoculation response 預防接種反應應急處理規程
Annual vaccine inoculations for pets 寵物一年一次的疫苗接種
Media report annual vaccine inoculations for pets may be too frequent 154新聞傳真寵物一年一次的疫苗接種可能過于頻繁
138 media report annual vaccine inoculations for pets may be too frequent 138新聞傳真寵物一年一次的疫苗接種可能過于頻繁
Investigation on viral hepatitis b infection and vaccine inoculation among pupils and high school students in karamy 克拉瑪依市中小學生乙型肝炎病毒感染調查
Epidemiological analysis of cases with rash and fever illness after measles vaccine inoculation during 1999 to 2002 in shandong province , china 接種麻疹疫苗后發熱出疹性病例的流行病學調查
Cientific research indicates that most annual vaccine inoculations for pets are not only unnecessary , but also waste money and can be potentially deadly 學研究指出,每年為寵物施以疫苗接種,絕大多數不僅沒有必要,而且是浪費金錢又可能有潛在的致命危險。
Vaccines for the most important pet diseases last three years or longer , and so annual vaccine inoculations are needless , and can even put pets at greater risk of vaccine - related problems 一年一次的疫苗接種是不需要的,而且將使得寵物冒著更大的危險,承受疫苗接種后所引發的相關問題。
A novel dynamic evolutionary clustering algorithm ( deca ) is proposed in this paper to overcome the shortcomings of fuzzy modeling method based on general clustering algorithms that fuzzy rule number should be determined beforehand . deca searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes ; at the same time , the convergence of clustering center parameters is expedited with the help of fuzzy c - means ( fcm ) algorithm . moreover , by introducing memory function and vaccine inoculation mechanism of immune system , at the same time , deca can converge to the optimal solution rapidly and stably . the proper fuzzy rule number and exact premise parameters are obtained simultaneously when using this efficient deca to identify fuzzy models . the effectiveness of the proposed fuzzy modeling method based on deca is demonstrated by simulation examples , and the accurate non - linear fuzzy models can be obtained when the method is applied to the thermal processes 針對模糊聚類算法不適應復雜環境的問題,提出了一種新的動態進化聚類算法,克服了傳統模糊聚類建模算法須事先確定規則數的缺陷.通過改進的遺傳策略來優化染色體長度,實現對聚類個數進行全局尋優;利用fcm算法加快聚類中心參數的收斂;并引入免疫系統的記憶功能和疫苗接種機理,使算法能快速穩定地收斂到最優解.利用這種高效的動態聚類算法辨識模糊模型,可同時得到合適的模糊規則數和準確的前提參數,將其應用于控制過程可獲得高精度的非線性模糊模型