The　concepts　of　five　parameters　of　nominal　water-cement　ratio,　equivalent　water-cement　ratio,　average　paste　thickness,　fly　ash-binder　ratio,　grain　volume　fraction　of　fine　aggregates　and　Modified　Tourfar＇s　Model　were　introduced.　It　was　verified　that　the　five　parameters　and　the　mix　proportion　of　concrete　can　be　transformed　each　other　when　Modified　Tourfar＇s　Model　is　applied.　The　behaviors　(strength,　slump,　et　al.)　of　concrete　primarily　determined　by　the　mix　proportion　of　concrete　now　depend　on　the　five　parameters.　The　prediction　models　of　strength　and　slump　of　concrete　were　built　based　on　artificial　neural　networks　(ANNs).　The　calculation　models　of　average　paste　thickness　and　equivalent　water-cement　ratio　can　be　obtained　by　the　reversal　deduction　of　the　two　prediction　models,　respectively.　A　concrete　mix　proportion　design　algorithm　based　on　a　way　from　aggregates　to　paste,　a　least　paste　content,　Modified　Tourfar＇s　Model　and　ANNs　was　proposed.　The　proposed　concrete　mix　proportion　design　algorithm　is　expected　to　reduce　the　number　of　trial　and　error,　save　cost,　laborers　and　time.　The　concrete　designed　by　the　proposed　algorithm　is　expected　to　have　lower　cement　and　water　contents,　higher　durability,　better　economical　and　ecological　effects.　©　2006　Elsevier　Ltd.　All　rights　reserved.